2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.patch_embed.proj.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.patch_embed.proj.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.patch_embed.proj.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.patch_embed.proj.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.patch_embed.norm.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.patch_embed.norm.weight: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.patch_embed.norm.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.patch_embed.norm.bias: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.0.blocks.0.norm1.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.0.blocks.0.norm1.weight: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.0.blocks.0.norm1.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.0.blocks.0.norm1.bias: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.0.blocks.0.attn.relative_position_bias_table: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.0.blocks.0.attn.relative_position_bias_table: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.0.blocks.0.attn.qkv.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.0.blocks.0.attn.qkv.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.0.blocks.0.attn.qkv.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.0.blocks.0.attn.qkv.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.0.blocks.0.attn.proj.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.0.blocks.0.attn.proj.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.0.blocks.0.attn.proj.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.0.blocks.0.attn.proj.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.0.blocks.0.norm2.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.0.blocks.0.norm2.weight: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.0.blocks.0.norm2.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.0.blocks.0.norm2.bias: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.0.blocks.0.mlp.fc1.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.0.blocks.0.mlp.fc1.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.0.blocks.0.mlp.fc1.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.0.blocks.0.mlp.fc1.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.0.blocks.0.mlp.fc2.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.0.blocks.0.mlp.fc2.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.0.blocks.0.mlp.fc2.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.0.blocks.0.mlp.fc2.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.0.blocks.1.norm1.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.0.blocks.1.norm1.weight: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.0.blocks.1.norm1.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.0.blocks.1.norm1.bias: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.0.blocks.1.attn.relative_position_bias_table: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.0.blocks.1.attn.relative_position_bias_table: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.0.blocks.1.attn.qkv.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.0.blocks.1.attn.qkv.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.0.blocks.1.attn.qkv.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.0.blocks.1.attn.qkv.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.0.blocks.1.attn.proj.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.0.blocks.1.attn.proj.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.0.blocks.1.attn.proj.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.0.blocks.1.attn.proj.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.0.blocks.1.norm2.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.0.blocks.1.norm2.weight: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.0.blocks.1.norm2.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.0.blocks.1.norm2.bias: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.0.blocks.1.mlp.fc1.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.0.blocks.1.mlp.fc1.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.0.blocks.1.mlp.fc1.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.0.blocks.1.mlp.fc1.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.0.blocks.1.mlp.fc2.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.0.blocks.1.mlp.fc2.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.0.blocks.1.mlp.fc2.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.0.blocks.1.mlp.fc2.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.0.downsample.reduction.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.0.downsample.reduction.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.0.downsample.norm.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.0.downsample.norm.weight: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.0.downsample.norm.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.0.downsample.norm.bias: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.1.blocks.0.norm1.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.1.blocks.0.norm1.weight: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.1.blocks.0.norm1.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.1.blocks.0.norm1.bias: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.1.blocks.0.attn.relative_position_bias_table: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.1.blocks.0.attn.relative_position_bias_table: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.1.blocks.0.attn.qkv.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.1.blocks.0.attn.qkv.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.1.blocks.0.attn.qkv.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.1.blocks.0.attn.qkv.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.1.blocks.0.attn.proj.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.1.blocks.0.attn.proj.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.1.blocks.0.attn.proj.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.1.blocks.0.attn.proj.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.1.blocks.0.norm2.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.1.blocks.0.norm2.weight: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.1.blocks.0.norm2.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.1.blocks.0.norm2.bias: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.1.blocks.0.mlp.fc1.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.1.blocks.0.mlp.fc1.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.1.blocks.0.mlp.fc1.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.1.blocks.0.mlp.fc1.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.1.blocks.0.mlp.fc2.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.1.blocks.0.mlp.fc2.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.1.blocks.0.mlp.fc2.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.1.blocks.0.mlp.fc2.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.1.blocks.1.norm1.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.1.blocks.1.norm1.weight: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.1.blocks.1.norm1.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.1.blocks.1.norm1.bias: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.1.blocks.1.attn.relative_position_bias_table: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.1.blocks.1.attn.relative_position_bias_table: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.1.blocks.1.attn.qkv.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.1.blocks.1.attn.qkv.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.1.blocks.1.attn.qkv.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.1.blocks.1.attn.qkv.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.1.blocks.1.attn.proj.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.1.blocks.1.attn.proj.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.1.blocks.1.attn.proj.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.1.blocks.1.attn.proj.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.1.blocks.1.norm2.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.1.blocks.1.norm2.weight: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.1.blocks.1.norm2.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.1.blocks.1.norm2.bias: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.1.blocks.1.mlp.fc1.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.1.blocks.1.mlp.fc1.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.1.blocks.1.mlp.fc1.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.1.blocks.1.mlp.fc1.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.1.blocks.1.mlp.fc2.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.1.blocks.1.mlp.fc2.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.1.blocks.1.mlp.fc2.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.1.blocks.1.mlp.fc2.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.1.downsample.reduction.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.1.downsample.reduction.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.1.downsample.norm.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.1.downsample.norm.weight: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.1.downsample.norm.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.1.downsample.norm.bias: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.0.norm1.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.0.norm1.weight: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.0.norm1.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.0.norm1.bias: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.0.attn.relative_position_bias_table: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.0.attn.relative_position_bias_table: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.0.attn.qkv.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.0.attn.qkv.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.0.attn.qkv.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.0.attn.qkv.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.0.attn.proj.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.0.attn.proj.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.0.attn.proj.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.0.attn.proj.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.0.norm2.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.0.norm2.weight: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.0.norm2.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.0.norm2.bias: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.0.mlp.fc1.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.0.mlp.fc1.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.0.mlp.fc1.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.0.mlp.fc1.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.0.mlp.fc2.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.0.mlp.fc2.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.0.mlp.fc2.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.0.mlp.fc2.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.1.norm1.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.1.norm1.weight: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.1.norm1.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.1.norm1.bias: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.1.attn.relative_position_bias_table: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.1.attn.relative_position_bias_table: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.1.attn.qkv.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.1.attn.qkv.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.1.attn.qkv.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.1.attn.qkv.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.1.attn.proj.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.1.attn.proj.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.1.attn.proj.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.1.attn.proj.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.1.norm2.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.1.norm2.weight: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.1.norm2.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.1.norm2.bias: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.1.mlp.fc1.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.1.mlp.fc1.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.1.mlp.fc1.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.1.mlp.fc1.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.1.mlp.fc2.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.1.mlp.fc2.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.1.mlp.fc2.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.1.mlp.fc2.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.2.norm1.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.2.norm1.weight: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.2.norm1.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.2.norm1.bias: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.2.attn.relative_position_bias_table: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.2.attn.relative_position_bias_table: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.2.attn.qkv.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.2.attn.qkv.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.2.attn.qkv.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.2.attn.qkv.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.2.attn.proj.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.2.attn.proj.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.2.attn.proj.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.2.attn.proj.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.2.norm2.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.2.norm2.weight: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.2.norm2.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.2.norm2.bias: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.2.mlp.fc1.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.2.mlp.fc1.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.2.mlp.fc1.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.2.mlp.fc1.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.2.mlp.fc2.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.2.mlp.fc2.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.2.mlp.fc2.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.2.mlp.fc2.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.3.norm1.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.3.norm1.weight: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.3.norm1.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.3.norm1.bias: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.3.attn.relative_position_bias_table: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.3.attn.relative_position_bias_table: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.3.attn.qkv.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.3.attn.qkv.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.3.attn.qkv.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.3.attn.qkv.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.3.attn.proj.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.3.attn.proj.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.3.attn.proj.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.3.attn.proj.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.3.norm2.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.3.norm2.weight: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.3.norm2.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.3.norm2.bias: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.3.mlp.fc1.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.3.mlp.fc1.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.3.mlp.fc1.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.3.mlp.fc1.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.3.mlp.fc2.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.3.mlp.fc2.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.3.mlp.fc2.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.3.mlp.fc2.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.4.norm1.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.4.norm1.weight: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.4.norm1.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.4.norm1.bias: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.4.attn.relative_position_bias_table: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.4.attn.relative_position_bias_table: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.4.attn.qkv.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.4.attn.qkv.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.4.attn.qkv.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.4.attn.qkv.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.4.attn.proj.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.4.attn.proj.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.4.attn.proj.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.4.attn.proj.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.4.norm2.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.4.norm2.weight: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.4.norm2.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.4.norm2.bias: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.4.mlp.fc1.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.4.mlp.fc1.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.4.mlp.fc1.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.4.mlp.fc1.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.4.mlp.fc2.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.4.mlp.fc2.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.4.mlp.fc2.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.4.mlp.fc2.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.5.norm1.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.5.norm1.weight: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.5.norm1.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.5.norm1.bias: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.5.attn.relative_position_bias_table: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.5.attn.relative_position_bias_table: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.5.attn.qkv.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.5.attn.qkv.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.5.attn.qkv.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.5.attn.qkv.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.5.attn.proj.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.5.attn.proj.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.5.attn.proj.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.5.attn.proj.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.5.norm2.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.5.norm2.weight: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.5.norm2.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.5.norm2.bias: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.5.mlp.fc1.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.5.mlp.fc1.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.5.mlp.fc1.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.5.mlp.fc1.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.5.mlp.fc2.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.5.mlp.fc2.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.5.mlp.fc2.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.5.mlp.fc2.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.6.norm1.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.6.norm1.weight: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.6.norm1.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.6.norm1.bias: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.6.attn.relative_position_bias_table: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.6.attn.relative_position_bias_table: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.6.attn.qkv.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.6.attn.qkv.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.6.attn.qkv.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.6.attn.qkv.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.6.attn.proj.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.6.attn.proj.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.6.attn.proj.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.6.attn.proj.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.6.norm2.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.6.norm2.weight: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.6.norm2.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.6.norm2.bias: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.6.mlp.fc1.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.6.mlp.fc1.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.6.mlp.fc1.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.6.mlp.fc1.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.6.mlp.fc2.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.6.mlp.fc2.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.6.mlp.fc2.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.6.mlp.fc2.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.7.norm1.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.7.norm1.weight: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.7.norm1.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.7.norm1.bias: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.7.attn.relative_position_bias_table: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.7.attn.relative_position_bias_table: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.7.attn.qkv.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.7.attn.qkv.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.7.attn.qkv.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.7.attn.qkv.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.7.attn.proj.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.7.attn.proj.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.7.attn.proj.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.7.attn.proj.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.7.norm2.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.7.norm2.weight: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.7.norm2.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.7.norm2.bias: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.7.mlp.fc1.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.7.mlp.fc1.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.7.mlp.fc1.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.7.mlp.fc1.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.7.mlp.fc2.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.7.mlp.fc2.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.7.mlp.fc2.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.7.mlp.fc2.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.8.norm1.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.8.norm1.weight: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.8.norm1.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.8.norm1.bias: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.8.attn.relative_position_bias_table: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.8.attn.relative_position_bias_table: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.8.attn.qkv.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.8.attn.qkv.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.8.attn.qkv.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.8.attn.qkv.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.8.attn.proj.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.8.attn.proj.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.8.attn.proj.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.8.attn.proj.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.8.norm2.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.8.norm2.weight: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.8.norm2.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.8.norm2.bias: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.8.mlp.fc1.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.8.mlp.fc1.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.8.mlp.fc1.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.8.mlp.fc1.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.8.mlp.fc2.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.8.mlp.fc2.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.8.mlp.fc2.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.8.mlp.fc2.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.9.norm1.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.9.norm1.weight: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.9.norm1.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.9.norm1.bias: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.9.attn.relative_position_bias_table: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.9.attn.relative_position_bias_table: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.9.attn.qkv.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.9.attn.qkv.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.9.attn.qkv.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.9.attn.qkv.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.9.attn.proj.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.9.attn.proj.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.9.attn.proj.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.9.attn.proj.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.9.norm2.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.9.norm2.weight: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.9.norm2.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.9.norm2.bias: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.9.mlp.fc1.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.9.mlp.fc1.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.9.mlp.fc1.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.9.mlp.fc1.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.9.mlp.fc2.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.9.mlp.fc2.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.9.mlp.fc2.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.9.mlp.fc2.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.10.norm1.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.10.norm1.weight: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.10.norm1.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.10.norm1.bias: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.10.attn.relative_position_bias_table: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.10.attn.relative_position_bias_table: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.10.attn.qkv.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.10.attn.qkv.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.10.attn.qkv.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.10.attn.qkv.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.10.attn.proj.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.10.attn.proj.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.10.attn.proj.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.10.attn.proj.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.10.norm2.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.10.norm2.weight: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.10.norm2.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.10.norm2.bias: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.10.mlp.fc1.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.10.mlp.fc1.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.10.mlp.fc1.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.10.mlp.fc1.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.10.mlp.fc2.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.10.mlp.fc2.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.10.mlp.fc2.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.10.mlp.fc2.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.11.norm1.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.11.norm1.weight: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.11.norm1.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.11.norm1.bias: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.11.attn.relative_position_bias_table: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.11.attn.relative_position_bias_table: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.11.attn.qkv.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.11.attn.qkv.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.11.attn.qkv.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.11.attn.qkv.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.11.attn.proj.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.11.attn.proj.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.11.attn.proj.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.11.attn.proj.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.11.norm2.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.11.norm2.weight: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.11.norm2.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.11.norm2.bias: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.11.mlp.fc1.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.11.mlp.fc1.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.11.mlp.fc1.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.11.mlp.fc1.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.11.mlp.fc2.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.11.mlp.fc2.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.11.mlp.fc2.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.11.mlp.fc2.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.12.norm1.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.12.norm1.weight: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.12.norm1.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.12.norm1.bias: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.12.attn.relative_position_bias_table: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.12.attn.relative_position_bias_table: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.12.attn.qkv.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.12.attn.qkv.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.12.attn.qkv.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.12.attn.qkv.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.12.attn.proj.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.12.attn.proj.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.12.attn.proj.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.12.attn.proj.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.12.norm2.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.12.norm2.weight: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.12.norm2.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.12.norm2.bias: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.12.mlp.fc1.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.12.mlp.fc1.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.12.mlp.fc1.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.12.mlp.fc1.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.12.mlp.fc2.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.12.mlp.fc2.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.12.mlp.fc2.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.12.mlp.fc2.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.13.norm1.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.13.norm1.weight: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.13.norm1.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.13.norm1.bias: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.13.attn.relative_position_bias_table: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.13.attn.relative_position_bias_table: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.13.attn.qkv.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.13.attn.qkv.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.13.attn.qkv.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.13.attn.qkv.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.13.attn.proj.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.13.attn.proj.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.13.attn.proj.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.13.attn.proj.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.13.norm2.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.13.norm2.weight: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.13.norm2.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.13.norm2.bias: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.13.mlp.fc1.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.13.mlp.fc1.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.13.mlp.fc1.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.13.mlp.fc1.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.13.mlp.fc2.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.13.mlp.fc2.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.13.mlp.fc2.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.13.mlp.fc2.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.14.norm1.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.14.norm1.weight: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.14.norm1.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.14.norm1.bias: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.14.attn.relative_position_bias_table: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.14.attn.relative_position_bias_table: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.14.attn.qkv.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.14.attn.qkv.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.14.attn.qkv.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.14.attn.qkv.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.14.attn.proj.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.14.attn.proj.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.14.attn.proj.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.14.attn.proj.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.14.norm2.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.14.norm2.weight: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.14.norm2.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.14.norm2.bias: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.14.mlp.fc1.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.14.mlp.fc1.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.14.mlp.fc1.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.14.mlp.fc1.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.14.mlp.fc2.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.14.mlp.fc2.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.14.mlp.fc2.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.14.mlp.fc2.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.15.norm1.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.15.norm1.weight: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.15.norm1.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.15.norm1.bias: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.15.attn.relative_position_bias_table: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.15.attn.relative_position_bias_table: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.15.attn.qkv.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.15.attn.qkv.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.15.attn.qkv.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.15.attn.qkv.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.15.attn.proj.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.15.attn.proj.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.15.attn.proj.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.15.attn.proj.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.15.norm2.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.15.norm2.weight: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.15.norm2.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.15.norm2.bias: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.15.mlp.fc1.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.15.mlp.fc1.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.15.mlp.fc1.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.15.mlp.fc1.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.15.mlp.fc2.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.15.mlp.fc2.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.15.mlp.fc2.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.15.mlp.fc2.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.16.norm1.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.16.norm1.weight: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.16.norm1.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.16.norm1.bias: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.16.attn.relative_position_bias_table: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.16.attn.relative_position_bias_table: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.16.attn.qkv.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.16.attn.qkv.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.16.attn.qkv.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.16.attn.qkv.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.16.attn.proj.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.16.attn.proj.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.16.attn.proj.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.16.attn.proj.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.16.norm2.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.16.norm2.weight: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.16.norm2.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.16.norm2.bias: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.16.mlp.fc1.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.16.mlp.fc1.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.16.mlp.fc1.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.16.mlp.fc1.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.16.mlp.fc2.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.16.mlp.fc2.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.16.mlp.fc2.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.16.mlp.fc2.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.17.norm1.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.17.norm1.weight: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.17.norm1.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.17.norm1.bias: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.17.attn.relative_position_bias_table: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.17.attn.relative_position_bias_table: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.17.attn.qkv.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.17.attn.qkv.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.17.attn.qkv.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.17.attn.qkv.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.17.attn.proj.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.17.attn.proj.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.17.attn.proj.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.17.attn.proj.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.17.norm2.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.17.norm2.weight: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.17.norm2.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.17.norm2.bias: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.17.mlp.fc1.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.17.mlp.fc1.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.17.mlp.fc1.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.17.mlp.fc1.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.17.mlp.fc2.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.17.mlp.fc2.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.17.mlp.fc2.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.blocks.17.mlp.fc2.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.downsample.reduction.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.downsample.reduction.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.downsample.norm.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.downsample.norm.weight: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.downsample.norm.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.2.downsample.norm.bias: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.3.blocks.0.norm1.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.3.blocks.0.norm1.weight: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.3.blocks.0.norm1.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.3.blocks.0.norm1.bias: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.3.blocks.0.attn.relative_position_bias_table: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.3.blocks.0.attn.relative_position_bias_table: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.3.blocks.0.attn.qkv.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.3.blocks.0.attn.qkv.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.3.blocks.0.attn.qkv.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.3.blocks.0.attn.qkv.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.3.blocks.0.attn.proj.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.3.blocks.0.attn.proj.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.3.blocks.0.attn.proj.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.3.blocks.0.attn.proj.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.3.blocks.0.norm2.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.3.blocks.0.norm2.weight: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.3.blocks.0.norm2.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.3.blocks.0.norm2.bias: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.3.blocks.0.mlp.fc1.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.3.blocks.0.mlp.fc1.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.3.blocks.0.mlp.fc1.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.3.blocks.0.mlp.fc1.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.3.blocks.0.mlp.fc2.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.3.blocks.0.mlp.fc2.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.3.blocks.0.mlp.fc2.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.3.blocks.0.mlp.fc2.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.3.blocks.1.norm1.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.3.blocks.1.norm1.weight: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.3.blocks.1.norm1.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.3.blocks.1.norm1.bias: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.3.blocks.1.attn.relative_position_bias_table: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.3.blocks.1.attn.relative_position_bias_table: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.3.blocks.1.attn.qkv.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.3.blocks.1.attn.qkv.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.3.blocks.1.attn.qkv.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.3.blocks.1.attn.qkv.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.3.blocks.1.attn.proj.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.3.blocks.1.attn.proj.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.3.blocks.1.attn.proj.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.3.blocks.1.attn.proj.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.3.blocks.1.norm2.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.3.blocks.1.norm2.weight: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.3.blocks.1.norm2.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.3.blocks.1.norm2.bias: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.3.blocks.1.mlp.fc1.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.3.blocks.1.mlp.fc1.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.3.blocks.1.mlp.fc1.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.3.blocks.1.mlp.fc1.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.3.blocks.1.mlp.fc2.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.3.blocks.1.mlp.fc2.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.3.blocks.1.mlp.fc2.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.layers.3.blocks.1.mlp.fc2.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.norm.weight: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.norm.weight: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.norm.bias: lr = 0.0001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- backbone.norm.bias: weight_decay = 0.0
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- cls_head.fc_cls.weight: lr = 0.001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- cls_head.fc_cls.weight: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- cls_head.fc_cls.bias: lr = 0.001
2022/08/01 19:29:23 - mmengine - INFO - paramwise_options -- cls_head.fc_cls.bias: weight_decay = 0.05
2022/08/01 19:29:23 - mmengine - INFO - load model from: https://github.com/SwinTransformer/storage/releases/download/v1.0.0/swin_base_patch4_window7_224.pth
2022/08/01 19:29:31 - mmengine - INFO - _IncompatibleKeys(missing_keys=['layers.0.blocks.0.attn.relative_position_index', 'layers.0.blocks.1.attn.relative_position_index', 'layers.1.blocks.0.attn.relative_position_index', 'layers.1.blocks.1.attn.relative_position_index', 'layers.2.blocks.0.attn.relative_position_index', 'layers.2.blocks.1.attn.relative_position_index', 'layers.2.blocks.2.attn.relative_position_index', 'layers.2.blocks.3.attn.relative_position_index', 'layers.2.blocks.4.attn.relative_position_index', 'layers.2.blocks.5.attn.relative_position_index', 'layers.2.blocks.6.attn.relative_position_index', 'layers.2.blocks.7.attn.relative_position_index', 'layers.2.blocks.8.attn.relative_position_index', 'layers.2.blocks.9.attn.relative_position_index', 'layers.2.blocks.10.attn.relative_position_index', 'layers.2.blocks.11.attn.relative_position_index', 'layers.2.blocks.12.attn.relative_position_index', 'layers.2.blocks.13.attn.relative_position_index', 'layers.2.blocks.14.attn.relative_position_index', 'layers.2.blocks.15.attn.relative_position_index', 'layers.2.blocks.16.attn.relative_position_index', 'layers.2.blocks.17.attn.relative_position_index', 'layers.3.blocks.0.attn.relative_position_index', 'layers.3.blocks.1.attn.relative_position_index'], unexpected_keys=['head.weight', 'head.bias'])
2022/08/01 19:29:31 - mmengine - INFO - => loaded successfully 'https://github.com/SwinTransformer/storage/releases/download/v1.0.0/swin_base_patch4_window7_224.pth'
2022/08/01 19:29:31 - mmengine - INFO - Checkpoints will be saved to /mnt/lustre/daiwenxun/X/mmaction2/work_dirs/swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb by HardDiskBackend.
2022/08/01 19:34:41 - mmengine - INFO - Epoch(train) [1][100/3757]  lr: 1.0949e-05  eta: 4 days, 1:02:14  time: 0.6854  data_time: 0.0110  memory: 45143  top1_acc: 0.0000  top5_acc: 0.2500  loss_cls: 5.7964  loss: 5.7964
2022/08/01 19:35:50 - mmengine - INFO - Epoch(train) [1][200/3757]  lr: 1.1907e-05  eta: 2 days, 11:15:34  time: 0.6847  data_time: 0.0104  memory: 45143  top1_acc: 0.1250  top5_acc: 0.3750  loss_cls: 5.2126  loss: 5.2126
2022/08/01 19:36:59 - mmengine - INFO - Epoch(train) [1][300/3757]  lr: 1.2865e-05  eta: 1 day, 22:39:57  time: 0.6864  data_time: 0.0114  memory: 45143  top1_acc: 0.0000  top5_acc: 0.1250  loss_cls: 4.4355  loss: 4.4355
2022/08/01 19:38:09 - mmengine - INFO - Epoch(train) [1][400/3757]  lr: 1.3824e-05  eta: 1 day, 16:22:06  time: 0.6875  data_time: 0.0125  memory: 45143  top1_acc: 0.2500  top5_acc: 0.7500  loss_cls: 3.9943  loss: 3.9943
2022/08/01 19:39:18 - mmengine - INFO - Epoch(train) [1][500/3757]  lr: 1.4782e-05  eta: 1 day, 12:34:14  time: 0.6934  data_time: 0.0122  memory: 45143  top1_acc: 0.2500  top5_acc: 0.6250  loss_cls: 3.4276  loss: 3.4276
2022/08/01 19:40:27 - mmengine - INFO - Epoch(train) [1][600/3757]  lr: 1.5740e-05  eta: 1 day, 10:02:07  time: 0.6901  data_time: 0.0118  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 3.2979  loss: 3.2979
2022/08/01 19:41:36 - mmengine - INFO - Epoch(train) [1][700/3757]  lr: 1.6699e-05  eta: 1 day, 8:14:01  time: 0.6941  data_time: 0.0134  memory: 45143  top1_acc: 0.3750  top5_acc: 0.6250  loss_cls: 3.2363  loss: 3.2363
2022/08/01 19:42:46 - mmengine - INFO - Epoch(train) [1][800/3757]  lr: 1.7657e-05  eta: 1 day, 6:52:26  time: 0.6873  data_time: 0.0123  memory: 45143  top1_acc: 0.3750  top5_acc: 0.3750  loss_cls: 2.9633  loss: 2.9633
2022/08/01 19:43:55 - mmengine - INFO - Epoch(train) [1][900/3757]  lr: 1.8615e-05  eta: 1 day, 5:48:12  time: 0.6862  data_time: 0.0120  memory: 45143  top1_acc: 0.1250  top5_acc: 0.7500  loss_cls: 3.3443  loss: 3.3443
2022/08/01 19:45:04 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/01 19:45:04 - mmengine - INFO - Epoch(train) [1][1000/3757]  lr: 1.9574e-05  eta: 1 day, 4:56:28  time: 0.6874  data_time: 0.0131  memory: 45143  top1_acc: 0.3750  top5_acc: 0.6250  loss_cls: 2.9178  loss: 2.9178
2022/08/01 19:46:13 - mmengine - INFO - Epoch(train) [1][1100/3757]  lr: 2.0532e-05  eta: 1 day, 4:14:04  time: 0.6926  data_time: 0.0145  memory: 45143  top1_acc: 0.3750  top5_acc: 0.6250  loss_cls: 3.0346  loss: 3.0346
2022/08/01 19:47:22 - mmengine - INFO - Epoch(train) [1][1200/3757]  lr: 2.1490e-05  eta: 1 day, 3:38:31  time: 0.6872  data_time: 0.0140  memory: 45143  top1_acc: 0.3750  top5_acc: 0.6250  loss_cls: 2.6097  loss: 2.6097
2022/08/01 19:48:31 - mmengine - INFO - Epoch(train) [1][1300/3757]  lr: 2.2448e-05  eta: 1 day, 3:08:06  time: 0.6906  data_time: 0.0127  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 2.9378  loss: 2.9378
2022/08/01 19:49:40 - mmengine - INFO - Epoch(train) [1][1400/3757]  lr: 2.3407e-05  eta: 1 day, 2:42:05  time: 0.6895  data_time: 0.0151  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 2.6888  loss: 2.6888
2022/08/01 19:50:49 - mmengine - INFO - Epoch(train) [1][1500/3757]  lr: 2.4365e-05  eta: 1 day, 2:19:15  time: 0.6908  data_time: 0.0154  memory: 45143  top1_acc: 0.2500  top5_acc: 0.8750  loss_cls: 2.8766  loss: 2.8766
2022/08/01 19:51:58 - mmengine - INFO - Epoch(train) [1][1600/3757]  lr: 2.5323e-05  eta: 1 day, 1:59:08  time: 0.6899  data_time: 0.0145  memory: 45143  top1_acc: 0.3750  top5_acc: 0.7500  loss_cls: 2.4362  loss: 2.4362
2022/08/01 19:53:08 - mmengine - INFO - Epoch(train) [1][1700/3757]  lr: 2.6282e-05  eta: 1 day, 1:41:42  time: 0.6941  data_time: 0.0152  memory: 45143  top1_acc: 0.5000  top5_acc: 0.5000  loss_cls: 2.5655  loss: 2.5655
2022/08/01 19:54:17 - mmengine - INFO - Epoch(train) [1][1800/3757]  lr: 2.7240e-05  eta: 1 day, 1:25:41  time: 0.6923  data_time: 0.0141  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 2.7197  loss: 2.7197
2022/08/01 19:55:26 - mmengine - INFO - Epoch(train) [1][1900/3757]  lr: 2.8198e-05  eta: 1 day, 1:11:11  time: 0.6870  data_time: 0.0129  memory: 45143  top1_acc: 0.2500  top5_acc: 0.6250  loss_cls: 2.5007  loss: 2.5007
2022/08/01 19:56:35 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/01 19:56:35 - mmengine - INFO - Epoch(train) [1][2000/3757]  lr: 2.9157e-05  eta: 1 day, 0:58:07  time: 0.6892  data_time: 0.0132  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 2.6715  loss: 2.6715
2022/08/01 19:57:44 - mmengine - INFO - Epoch(train) [1][2100/3757]  lr: 3.0115e-05  eta: 1 day, 0:46:26  time: 0.6901  data_time: 0.0154  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 2.4434  loss: 2.4434
2022/08/01 19:58:54 - mmengine - INFO - Epoch(train) [1][2200/3757]  lr: 3.1073e-05  eta: 1 day, 0:35:39  time: 0.6898  data_time: 0.0132  memory: 45143  top1_acc: 0.3750  top5_acc: 0.7500  loss_cls: 2.3403  loss: 2.3403
2022/08/01 20:00:03 - mmengine - INFO - Epoch(train) [1][2300/3757]  lr: 3.2032e-05  eta: 1 day, 0:25:31  time: 0.6913  data_time: 0.0139  memory: 45143  top1_acc: 0.6250  top5_acc: 1.0000  loss_cls: 2.5129  loss: 2.5129
2022/08/01 20:01:12 - mmengine - INFO - Epoch(train) [1][2400/3757]  lr: 3.2990e-05  eta: 1 day, 0:16:29  time: 0.6912  data_time: 0.0146  memory: 45143  top1_acc: 0.2500  top5_acc: 0.7500  loss_cls: 2.7734  loss: 2.7734
2022/08/01 20:02:22 - mmengine - INFO - Epoch(train) [1][2500/3757]  lr: 3.3948e-05  eta: 1 day, 0:08:05  time: 0.6904  data_time: 0.0151  memory: 45143  top1_acc: 0.5000  top5_acc: 1.0000  loss_cls: 2.2973  loss: 2.2973
2022/08/01 20:03:31 - mmengine - INFO - Epoch(train) [1][2600/3757]  lr: 3.4907e-05  eta: 23:59:56  time: 0.6945  data_time: 0.0148  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 2.4253  loss: 2.4253
2022/08/01 20:04:40 - mmengine - INFO - Epoch(train) [1][2700/3757]  lr: 3.5865e-05  eta: 23:52:25  time: 0.6897  data_time: 0.0147  memory: 45143  top1_acc: 0.5000  top5_acc: 1.0000  loss_cls: 2.2737  loss: 2.2737
2022/08/01 20:05:50 - mmengine - INFO - Epoch(train) [1][2800/3757]  lr: 3.6823e-05  eta: 23:45:31  time: 0.6977  data_time: 0.0148  memory: 45143  top1_acc: 0.3750  top5_acc: 0.7500  loss_cls: 2.4320  loss: 2.4320
2022/08/01 20:06:59 - mmengine - INFO - Epoch(train) [1][2900/3757]  lr: 3.7782e-05  eta: 23:38:54  time: 0.6985  data_time: 0.0143  memory: 45143  top1_acc: 0.5000  top5_acc: 0.6250  loss_cls: 2.1202  loss: 2.1202
2022/08/01 20:08:09 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/01 20:08:09 - mmengine - INFO - Epoch(train) [1][3000/3757]  lr: 3.8740e-05  eta: 23:33:02  time: 0.6910  data_time: 0.0146  memory: 45143  top1_acc: 0.6250  top5_acc: 1.0000  loss_cls: 2.3070  loss: 2.3070
2022/08/01 20:09:19 - mmengine - INFO - Epoch(train) [1][3100/3757]  lr: 3.9698e-05  eta: 23:26:57  time: 0.6898  data_time: 0.0130  memory: 45143  top1_acc: 0.2500  top5_acc: 0.7500  loss_cls: 2.5340  loss: 2.5340
2022/08/01 20:10:28 - mmengine - INFO - Epoch(train) [1][3200/3757]  lr: 4.0656e-05  eta: 23:21:35  time: 0.7032  data_time: 0.0164  memory: 45143  top1_acc: 0.2500  top5_acc: 0.6250  loss_cls: 2.5893  loss: 2.5893
2022/08/01 20:11:38 - mmengine - INFO - Epoch(train) [1][3300/3757]  lr: 4.1615e-05  eta: 23:16:09  time: 0.6888  data_time: 0.0138  memory: 45143  top1_acc: 0.5000  top5_acc: 0.5000  loss_cls: 2.5053  loss: 2.5053
2022/08/01 20:12:47 - mmengine - INFO - Epoch(train) [1][3400/3757]  lr: 4.2573e-05  eta: 23:11:02  time: 0.6940  data_time: 0.0147  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 2.7590  loss: 2.7590
2022/08/01 20:13:56 - mmengine - INFO - Epoch(train) [1][3500/3757]  lr: 4.3531e-05  eta: 23:06:09  time: 0.6880  data_time: 0.0134  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 1.9680  loss: 1.9680
2022/08/01 20:15:06 - mmengine - INFO - Epoch(train) [1][3600/3757]  lr: 4.4490e-05  eta: 23:01:20  time: 0.6905  data_time: 0.0138  memory: 45143  top1_acc: 0.2500  top5_acc: 0.3750  loss_cls: 2.3583  loss: 2.3583
2022/08/01 20:16:16 - mmengine - INFO - Epoch(train) [1][3700/3757]  lr: 4.5448e-05  eta: 22:57:25  time: 0.7006  data_time: 0.0136  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 2.4734  loss: 2.4734
2022/08/01 20:16:56 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/01 20:16:56 - mmengine - INFO - Epoch(train) [1][3757/3757]  lr: 4.5994e-05  eta: 22:55:43  time: 0.6810  data_time: 0.0137  memory: 45143  top1_acc: 0.4286  top5_acc: 1.0000  loss_cls: 2.2938  loss: 2.2938
2022/08/01 20:18:08 - mmengine - INFO - Epoch(train) [2][100/3757]  lr: 4.6824e-05  eta: 22:46:04  time: 0.6909  data_time: 0.0136  memory: 45143  top1_acc: 0.3750  top5_acc: 0.7500  loss_cls: 1.9954  loss: 1.9954
2022/08/01 20:19:17 - mmengine - INFO - Epoch(train) [2][200/3757]  lr: 4.7780e-05  eta: 22:42:01  time: 0.6917  data_time: 0.0146  memory: 45143  top1_acc: 0.2500  top5_acc: 0.6250  loss_cls: 2.0435  loss: 2.0435
2022/08/01 20:19:48 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/01 20:20:28 - mmengine - INFO - Epoch(train) [2][300/3757]  lr: 4.8735e-05  eta: 22:38:48  time: 0.6876  data_time: 0.0145  memory: 45143  top1_acc: 0.5000  top5_acc: 0.8750  loss_cls: 2.1839  loss: 2.1839
2022/08/01 20:21:37 - mmengine - INFO - Epoch(train) [2][400/3757]  lr: 4.9691e-05  eta: 22:35:06  time: 0.6903  data_time: 0.0139  memory: 45143  top1_acc: 0.3750  top5_acc: 0.7500  loss_cls: 1.9688  loss: 1.9688
2022/08/01 20:22:52 - mmengine - INFO - Epoch(train) [2][500/3757]  lr: 5.0647e-05  eta: 22:33:35  time: 0.6902  data_time: 0.0143  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 2.4127  loss: 2.4127
2022/08/01 20:24:01 - mmengine - INFO - Epoch(train) [2][600/3757]  lr: 5.1602e-05  eta: 22:29:54  time: 0.6914  data_time: 0.0143  memory: 45143  top1_acc: 0.3750  top5_acc: 0.5000  loss_cls: 2.5081  loss: 2.5081
2022/08/01 20:25:10 - mmengine - INFO - Epoch(train) [2][700/3757]  lr: 5.2558e-05  eta: 22:26:38  time: 0.6887  data_time: 0.0146  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 2.4414  loss: 2.4414
2022/08/01 20:26:19 - mmengine - INFO - Epoch(train) [2][800/3757]  lr: 5.3514e-05  eta: 22:23:12  time: 0.6894  data_time: 0.0145  memory: 45143  top1_acc: 0.3750  top5_acc: 0.6250  loss_cls: 2.3276  loss: 2.3276
2022/08/01 20:27:29 - mmengine - INFO - Epoch(train) [2][900/3757]  lr: 5.4469e-05  eta: 22:20:01  time: 0.6908  data_time: 0.0133  memory: 45143  top1_acc: 0.3750  top5_acc: 0.6250  loss_cls: 2.0544  loss: 2.0544
2022/08/01 20:28:38 - mmengine - INFO - Epoch(train) [2][1000/3757]  lr: 5.5425e-05  eta: 22:16:51  time: 0.6903  data_time: 0.0150  memory: 45143  top1_acc: 0.3750  top5_acc: 1.0000  loss_cls: 2.1637  loss: 2.1637
2022/08/01 20:29:48 - mmengine - INFO - Epoch(train) [2][1100/3757]  lr: 5.6381e-05  eta: 22:13:49  time: 0.6978  data_time: 0.0136  memory: 45143  top1_acc: 0.3750  top5_acc: 0.6250  loss_cls: 1.9107  loss: 1.9107
2022/08/01 20:30:57 - mmengine - INFO - Epoch(train) [2][1200/3757]  lr: 5.7337e-05  eta: 22:10:59  time: 0.6927  data_time: 0.0154  memory: 45143  top1_acc: 0.5000  top5_acc: 0.6250  loss_cls: 2.3935  loss: 2.3935
2022/08/01 20:31:27 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/01 20:32:07 - mmengine - INFO - Epoch(train) [2][1300/3757]  lr: 5.8292e-05  eta: 22:08:03  time: 0.6890  data_time: 0.0136  memory: 45143  top1_acc: 0.7500  top5_acc: 0.7500  loss_cls: 2.0617  loss: 2.0617
2022/08/01 20:33:16 - mmengine - INFO - Epoch(train) [2][1400/3757]  lr: 5.9248e-05  eta: 22:05:09  time: 0.6942  data_time: 0.0158  memory: 45143  top1_acc: 0.5000  top5_acc: 1.0000  loss_cls: 2.0988  loss: 2.0988
2022/08/01 20:34:25 - mmengine - INFO - Epoch(train) [2][1500/3757]  lr: 6.0204e-05  eta: 22:02:20  time: 0.6898  data_time: 0.0141  memory: 45143  top1_acc: 0.1250  top5_acc: 0.7500  loss_cls: 2.1698  loss: 2.1698
2022/08/01 20:35:35 - mmengine - INFO - Epoch(train) [2][1600/3757]  lr: 6.1159e-05  eta: 21:59:33  time: 0.6929  data_time: 0.0149  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 2.1560  loss: 2.1560
2022/08/01 20:36:44 - mmengine - INFO - Epoch(train) [2][1700/3757]  lr: 6.2115e-05  eta: 21:56:54  time: 0.6920  data_time: 0.0146  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 2.1944  loss: 2.1944
2022/08/01 20:37:53 - mmengine - INFO - Epoch(train) [2][1800/3757]  lr: 6.3071e-05  eta: 21:54:21  time: 0.6961  data_time: 0.0163  memory: 45143  top1_acc: 0.3750  top5_acc: 0.7500  loss_cls: 2.1560  loss: 2.1560
2022/08/01 20:39:03 - mmengine - INFO - Epoch(train) [2][1900/3757]  lr: 6.4026e-05  eta: 21:51:46  time: 0.6944  data_time: 0.0154  memory: 45143  top1_acc: 0.3750  top5_acc: 0.6250  loss_cls: 2.1761  loss: 2.1761
2022/08/01 20:40:13 - mmengine - INFO - Epoch(train) [2][2000/3757]  lr: 6.4982e-05  eta: 21:49:22  time: 0.6990  data_time: 0.0157  memory: 45143  top1_acc: 0.5000  top5_acc: 0.8750  loss_cls: 2.2813  loss: 2.2813
2022/08/01 20:41:22 - mmengine - INFO - Epoch(train) [2][2100/3757]  lr: 6.5938e-05  eta: 21:46:55  time: 0.6927  data_time: 0.0146  memory: 45143  top1_acc: 0.7500  top5_acc: 0.7500  loss_cls: 2.1832  loss: 2.1832
2022/08/01 20:42:31 - mmengine - INFO - Epoch(train) [2][2200/3757]  lr: 6.6893e-05  eta: 21:44:30  time: 0.6919  data_time: 0.0142  memory: 45143  top1_acc: 0.5000  top5_acc: 0.6250  loss_cls: 2.1628  loss: 2.1628
2022/08/01 20:43:01 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/01 20:43:41 - mmengine - INFO - Epoch(train) [2][2300/3757]  lr: 6.7849e-05  eta: 21:42:16  time: 0.6992  data_time: 0.0153  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 2.0224  loss: 2.0224
2022/08/01 20:44:51 - mmengine - INFO - Epoch(train) [2][2400/3757]  lr: 6.8805e-05  eta: 21:40:00  time: 0.6897  data_time: 0.0142  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 2.2284  loss: 2.2284
2022/08/01 20:46:00 - mmengine - INFO - Epoch(train) [2][2500/3757]  lr: 6.9760e-05  eta: 21:37:43  time: 0.6948  data_time: 0.0146  memory: 45143  top1_acc: 0.5000  top5_acc: 0.5000  loss_cls: 2.1292  loss: 2.1292
2022/08/01 20:47:10 - mmengine - INFO - Epoch(train) [2][2600/3757]  lr: 7.0716e-05  eta: 21:35:27  time: 0.6901  data_time: 0.0139  memory: 45143  top1_acc: 0.2500  top5_acc: 0.6250  loss_cls: 2.4249  loss: 2.4249
2022/08/01 20:48:19 - mmengine - INFO - Epoch(train) [2][2700/3757]  lr: 7.1672e-05  eta: 21:33:14  time: 0.6934  data_time: 0.0144  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 1.9708  loss: 1.9708
2022/08/01 20:49:29 - mmengine - INFO - Epoch(train) [2][2800/3757]  lr: 7.2628e-05  eta: 21:31:02  time: 0.6901  data_time: 0.0137  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 1.9703  loss: 1.9703
2022/08/01 20:50:38 - mmengine - INFO - Epoch(train) [2][2900/3757]  lr: 7.3583e-05  eta: 21:28:58  time: 0.6958  data_time: 0.0159  memory: 45143  top1_acc: 0.2500  top5_acc: 0.7500  loss_cls: 2.4826  loss: 2.4826
2022/08/01 20:51:48 - mmengine - INFO - Epoch(train) [2][3000/3757]  lr: 7.4539e-05  eta: 21:26:53  time: 0.6936  data_time: 0.0159  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 2.0167  loss: 2.0167
2022/08/01 20:52:58 - mmengine - INFO - Epoch(train) [2][3100/3757]  lr: 7.5495e-05  eta: 21:24:50  time: 0.6896  data_time: 0.0149  memory: 45143  top1_acc: 0.5000  top5_acc: 0.6250  loss_cls: 2.1040  loss: 2.1040
2022/08/01 20:54:07 - mmengine - INFO - Epoch(train) [2][3200/3757]  lr: 7.6450e-05  eta: 21:22:50  time: 0.6913  data_time: 0.0147  memory: 45143  top1_acc: 0.5000  top5_acc: 0.6250  loss_cls: 2.0509  loss: 2.0509
2022/08/01 20:54:37 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/01 20:55:17 - mmengine - INFO - Epoch(train) [2][3300/3757]  lr: 7.7406e-05  eta: 21:20:47  time: 0.6911  data_time: 0.0123  memory: 45143  top1_acc: 0.2500  top5_acc: 0.5000  loss_cls: 1.9714  loss: 1.9714
2022/08/01 20:56:26 - mmengine - INFO - Epoch(train) [2][3400/3757]  lr: 7.8362e-05  eta: 21:18:42  time: 0.6993  data_time: 0.0158  memory: 45143  top1_acc: 0.5000  top5_acc: 0.6250  loss_cls: 2.2232  loss: 2.2232
2022/08/01 20:57:36 - mmengine - INFO - Epoch(train) [2][3500/3757]  lr: 7.9317e-05  eta: 21:16:52  time: 0.7138  data_time: 0.0143  memory: 45143  top1_acc: 0.5000  top5_acc: 0.6250  loss_cls: 2.3893  loss: 2.3893
2022/08/01 20:58:47 - mmengine - INFO - Epoch(train) [2][3600/3757]  lr: 8.0273e-05  eta: 21:15:15  time: 0.6902  data_time: 0.0109  memory: 45143  top1_acc: 0.5000  top5_acc: 1.0000  loss_cls: 1.9929  loss: 1.9929
2022/08/01 20:59:58 - mmengine - INFO - Epoch(train) [2][3700/3757]  lr: 8.1229e-05  eta: 21:13:37  time: 0.6912  data_time: 0.0152  memory: 45143  top1_acc: 0.1250  top5_acc: 0.3750  loss_cls: 2.3313  loss: 2.3313
2022/08/01 21:00:38 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/01 21:00:38 - mmengine - INFO - Epoch(train) [2][3757/3757]  lr: 8.1773e-05  eta: 21:12:49  time: 0.7091  data_time: 0.0166  memory: 45143  top1_acc: 0.1429  top5_acc: 0.8571  loss_cls: 2.2057  loss: 2.2057
2022/08/01 21:01:50 - mmengine - INFO - Epoch(train) [3][100/3757]  lr: 8.2050e-05  eta: 21:08:23  time: 0.6884  data_time: 0.0141  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 2.2430  loss: 2.2430
2022/08/01 21:02:59 - mmengine - INFO - Epoch(train) [3][200/3757]  lr: 8.2998e-05  eta: 21:06:36  time: 0.6961  data_time: 0.0152  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.9089  loss: 1.9089
2022/08/01 21:04:09 - mmengine - INFO - Epoch(train) [3][300/3757]  lr: 8.3946e-05  eta: 21:04:46  time: 0.6882  data_time: 0.0138  memory: 45143  top1_acc: 0.5000  top5_acc: 0.6250  loss_cls: 2.1616  loss: 2.1616
2022/08/01 21:05:19 - mmengine - INFO - Epoch(train) [3][400/3757]  lr: 8.4894e-05  eta: 21:02:58  time: 0.6956  data_time: 0.0163  memory: 45143  top1_acc: 0.3750  top5_acc: 0.8750  loss_cls: 2.0688  loss: 2.0688
2022/08/01 21:06:18 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/01 21:06:28 - mmengine - INFO - Epoch(train) [3][500/3757]  lr: 8.5841e-05  eta: 21:01:09  time: 0.6895  data_time: 0.0149  memory: 45143  top1_acc: 0.3750  top5_acc: 0.6250  loss_cls: 2.0570  loss: 2.0570
2022/08/01 21:07:38 - mmengine - INFO - Epoch(train) [3][600/3757]  lr: 8.6789e-05  eta: 20:59:19  time: 0.6907  data_time: 0.0155  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 2.2170  loss: 2.2170
2022/08/01 21:08:47 - mmengine - INFO - Epoch(train) [3][700/3757]  lr: 8.7737e-05  eta: 20:57:29  time: 0.6966  data_time: 0.0156  memory: 45143  top1_acc: 0.3750  top5_acc: 0.7500  loss_cls: 2.1639  loss: 2.1639
2022/08/01 21:09:57 - mmengine - INFO - Epoch(train) [3][800/3757]  lr: 8.8685e-05  eta: 20:55:53  time: 0.7068  data_time: 0.0154  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 2.1334  loss: 2.1334
2022/08/01 21:11:06 - mmengine - INFO - Epoch(train) [3][900/3757]  lr: 8.9633e-05  eta: 20:54:04  time: 0.6940  data_time: 0.0156  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 2.0814  loss: 2.0814
2022/08/01 21:12:16 - mmengine - INFO - Epoch(train) [3][1000/3757]  lr: 9.0581e-05  eta: 20:52:21  time: 0.6948  data_time: 0.0157  memory: 45143  top1_acc: 0.3750  top5_acc: 1.0000  loss_cls: 1.8566  loss: 1.8566
2022/08/01 21:13:25 - mmengine - INFO - Epoch(train) [3][1100/3757]  lr: 9.1528e-05  eta: 20:50:36  time: 0.7012  data_time: 0.0165  memory: 45143  top1_acc: 0.3750  top5_acc: 0.5000  loss_cls: 2.1433  loss: 2.1433
2022/08/01 21:14:35 - mmengine - INFO - Epoch(train) [3][1200/3757]  lr: 9.2476e-05  eta: 20:48:57  time: 0.6983  data_time: 0.0143  memory: 45143  top1_acc: 0.6250  top5_acc: 0.6250  loss_cls: 2.0428  loss: 2.0428
2022/08/01 21:15:45 - mmengine - INFO - Epoch(train) [3][1300/3757]  lr: 9.3424e-05  eta: 20:47:22  time: 0.7073  data_time: 0.0162  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 2.0387  loss: 2.0387
2022/08/01 21:16:55 - mmengine - INFO - Epoch(train) [3][1400/3757]  lr: 9.4372e-05  eta: 20:45:48  time: 0.7062  data_time: 0.0158  memory: 45143  top1_acc: 0.5000  top5_acc: 0.6250  loss_cls: 2.0194  loss: 2.0194
2022/08/01 21:17:55 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/01 21:18:05 - mmengine - INFO - Epoch(train) [3][1500/3757]  lr: 9.5320e-05  eta: 20:44:09  time: 0.6922  data_time: 0.0152  memory: 45143  top1_acc: 0.5000  top5_acc: 0.5000  loss_cls: 2.2498  loss: 2.2498
2022/08/01 21:19:15 - mmengine - INFO - Epoch(train) [3][1600/3757]  lr: 9.6268e-05  eta: 20:42:28  time: 0.6901  data_time: 0.0138  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 2.2554  loss: 2.2554
2022/08/01 21:20:24 - mmengine - INFO - Epoch(train) [3][1700/3757]  lr: 9.7215e-05  eta: 20:40:52  time: 0.6922  data_time: 0.0149  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 2.2230  loss: 2.2230
2022/08/01 21:21:34 - mmengine - INFO - Epoch(train) [3][1800/3757]  lr: 9.8163e-05  eta: 20:39:15  time: 0.6890  data_time: 0.0144  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.9832  loss: 1.9832
2022/08/01 21:22:44 - mmengine - INFO - Epoch(train) [3][1900/3757]  lr: 9.8912e-05  eta: 20:37:37  time: 0.6953  data_time: 0.0158  memory: 45143  top1_acc: 0.5000  top5_acc: 0.6250  loss_cls: 2.1629  loss: 2.1629
2022/08/01 21:23:53 - mmengine - INFO - Epoch(train) [3][2000/3757]  lr: 9.8912e-05  eta: 20:36:00  time: 0.6889  data_time: 0.0140  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 2.1083  loss: 2.1083
2022/08/01 21:25:03 - mmengine - INFO - Epoch(train) [3][2100/3757]  lr: 9.8912e-05  eta: 20:34:23  time: 0.6909  data_time: 0.0154  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.9672  loss: 1.9672
2022/08/01 21:26:12 - mmengine - INFO - Epoch(train) [3][2200/3757]  lr: 9.8912e-05  eta: 20:32:45  time: 0.6885  data_time: 0.0138  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 2.0539  loss: 2.0539
2022/08/01 21:27:22 - mmengine - INFO - Epoch(train) [3][2300/3757]  lr: 9.8912e-05  eta: 20:31:12  time: 0.6958  data_time: 0.0145  memory: 45143  top1_acc: 0.3750  top5_acc: 0.7500  loss_cls: 2.4998  loss: 2.4998
2022/08/01 21:28:32 - mmengine - INFO - Epoch(train) [3][2400/3757]  lr: 9.8912e-05  eta: 20:29:39  time: 0.6881  data_time: 0.0136  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 2.3557  loss: 2.3557
2022/08/01 21:29:31 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/01 21:29:41 - mmengine - INFO - Epoch(train) [3][2500/3757]  lr: 9.8912e-05  eta: 20:28:04  time: 0.6969  data_time: 0.0132  memory: 45143  top1_acc: 0.6250  top5_acc: 0.6250  loss_cls: 1.9525  loss: 1.9525
2022/08/01 21:30:51 - mmengine - INFO - Epoch(train) [3][2600/3757]  lr: 9.8912e-05  eta: 20:26:36  time: 0.6894  data_time: 0.0149  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 2.1431  loss: 2.1431
2022/08/01 21:32:01 - mmengine - INFO - Epoch(train) [3][2700/3757]  lr: 9.8912e-05  eta: 20:25:04  time: 0.6910  data_time: 0.0157  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.8417  loss: 1.8417
2022/08/01 21:33:10 - mmengine - INFO - Epoch(train) [3][2800/3757]  lr: 9.8912e-05  eta: 20:23:30  time: 0.6940  data_time: 0.0156  memory: 45143  top1_acc: 0.3750  top5_acc: 0.5000  loss_cls: 1.9025  loss: 1.9025
2022/08/01 21:34:20 - mmengine - INFO - Epoch(train) [3][2900/3757]  lr: 9.8912e-05  eta: 20:22:01  time: 0.6987  data_time: 0.0156  memory: 45143  top1_acc: 0.3750  top5_acc: 0.6250  loss_cls: 2.2039  loss: 2.2039
2022/08/01 21:35:30 - mmengine - INFO - Epoch(train) [3][3000/3757]  lr: 9.8912e-05  eta: 20:20:26  time: 0.6943  data_time: 0.0152  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 2.2546  loss: 2.2546
2022/08/01 21:36:39 - mmengine - INFO - Epoch(train) [3][3100/3757]  lr: 9.8912e-05  eta: 20:18:55  time: 0.6992  data_time: 0.0156  memory: 45143  top1_acc: 0.3750  top5_acc: 0.6250  loss_cls: 1.8765  loss: 1.8765
2022/08/01 21:37:49 - mmengine - INFO - Epoch(train) [3][3200/3757]  lr: 9.8912e-05  eta: 20:17:22  time: 0.6944  data_time: 0.0164  memory: 45143  top1_acc: 0.3750  top5_acc: 0.8750  loss_cls: 2.3013  loss: 2.3013
2022/08/01 21:38:58 - mmengine - INFO - Epoch(train) [3][3300/3757]  lr: 9.8912e-05  eta: 20:15:50  time: 0.6941  data_time: 0.0156  memory: 45143  top1_acc: 0.3750  top5_acc: 0.6250  loss_cls: 2.1919  loss: 2.1919
2022/08/01 21:40:08 - mmengine - INFO - Epoch(train) [3][3400/3757]  lr: 9.8912e-05  eta: 20:14:19  time: 0.6930  data_time: 0.0158  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.8886  loss: 1.8886
2022/08/01 21:41:08 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/01 21:41:17 - mmengine - INFO - Epoch(train) [3][3500/3757]  lr: 9.8912e-05  eta: 20:12:49  time: 0.6992  data_time: 0.0146  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 2.1110  loss: 2.1110
2022/08/01 21:42:28 - mmengine - INFO - Epoch(train) [3][3600/3757]  lr: 9.8912e-05  eta: 20:11:25  time: 0.6961  data_time: 0.0152  memory: 45143  top1_acc: 0.3750  top5_acc: 0.6250  loss_cls: 2.0629  loss: 2.0629
2022/08/01 21:43:38 - mmengine - INFO - Epoch(train) [3][3700/3757]  lr: 9.8912e-05  eta: 20:10:00  time: 0.6931  data_time: 0.0152  memory: 45143  top1_acc: 0.3750  top5_acc: 0.8750  loss_cls: 2.0276  loss: 2.0276
2022/08/01 21:44:17 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/01 21:44:17 - mmengine - INFO - Epoch(train) [3][3757/3757]  lr: 9.8912e-05  eta: 20:09:26  time: 0.6782  data_time: 0.0145  memory: 45143  top1_acc: 0.2857  top5_acc: 0.8571  loss_cls: 2.1884  loss: 2.1884
2022/08/01 21:44:17 - mmengine - INFO - Saving checkpoint at 3 epochs
2022/08/01 21:46:54 - mmengine - INFO - Epoch(val) [3][100/310]    eta: 0:00:55  time: 0.2663  data_time: 0.0099  memory: 8742  
2022/08/01 21:47:22 - mmengine - INFO - Epoch(val) [3][200/310]    eta: 0:00:30  time: 0.2816  data_time: 0.0138  memory: 8742  
2022/08/01 21:47:49 - mmengine - INFO - Epoch(val) [3][300/310]    eta: 0:00:02  time: 0.2630  data_time: 0.0103  memory: 8742  
2022/08/01 21:47:53 - mmengine - INFO - Epoch(val) [3][310/310]  acc/top1: 0.6100  acc/top5: 0.8443  acc/mean1: 0.6099
2022/08/01 21:47:55 - mmengine - INFO - The best checkpoint with 0.6100 acc/top1 at 4 epoch is saved to best_acc/top1_epoch_4.pth.
2022/08/01 21:49:05 - mmengine - INFO - Epoch(train) [4][100/3757]  lr: 9.7558e-05  eta: 20:06:00  time: 0.6876  data_time: 0.0148  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 2.1678  loss: 2.1678
2022/08/01 21:50:15 - mmengine - INFO - Epoch(train) [4][200/3757]  lr: 9.7558e-05  eta: 20:04:35  time: 0.7082  data_time: 0.0162  memory: 45143  top1_acc: 0.7500  top5_acc: 0.7500  loss_cls: 1.9501  loss: 1.9501
2022/08/01 21:51:25 - mmengine - INFO - Epoch(train) [4][300/3757]  lr: 9.7558e-05  eta: 20:03:10  time: 0.6878  data_time: 0.0144  memory: 45143  top1_acc: 0.2500  top5_acc: 0.5000  loss_cls: 1.9316  loss: 1.9316
2022/08/01 21:52:35 - mmengine - INFO - Epoch(train) [4][400/3757]  lr: 9.7558e-05  eta: 20:01:45  time: 0.6921  data_time: 0.0153  memory: 45143  top1_acc: 0.7500  top5_acc: 0.7500  loss_cls: 1.9154  loss: 1.9154
2022/08/01 21:53:44 - mmengine - INFO - Epoch(train) [4][500/3757]  lr: 9.7558e-05  eta: 20:00:14  time: 0.6887  data_time: 0.0143  memory: 45143  top1_acc: 0.3750  top5_acc: 0.3750  loss_cls: 1.8338  loss: 1.8338
2022/08/01 21:54:53 - mmengine - INFO - Epoch(train) [4][600/3757]  lr: 9.7558e-05  eta: 19:58:44  time: 0.6903  data_time: 0.0153  memory: 45143  top1_acc: 0.5000  top5_acc: 0.5000  loss_cls: 2.0752  loss: 2.0752
2022/08/01 21:56:03 - mmengine - INFO - Epoch(train) [4][700/3757]  lr: 9.7558e-05  eta: 19:57:16  time: 0.7054  data_time: 0.0156  memory: 45143  top1_acc: 0.7500  top5_acc: 0.7500  loss_cls: 1.9464  loss: 1.9464
2022/08/01 21:56:23 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/01 21:57:12 - mmengine - INFO - Epoch(train) [4][800/3757]  lr: 9.7558e-05  eta: 19:55:50  time: 0.6911  data_time: 0.0158  memory: 45143  top1_acc: 0.5000  top5_acc: 0.8750  loss_cls: 1.9347  loss: 1.9347
2022/08/01 21:58:21 - mmengine - INFO - Epoch(train) [4][900/3757]  lr: 9.7558e-05  eta: 19:54:23  time: 0.6922  data_time: 0.0158  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 2.0500  loss: 2.0500
2022/08/01 21:59:31 - mmengine - INFO - Epoch(train) [4][1000/3757]  lr: 9.7558e-05  eta: 19:52:55  time: 0.6938  data_time: 0.0155  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.9078  loss: 1.9078
2022/08/01 22:00:40 - mmengine - INFO - Epoch(train) [4][1100/3757]  lr: 9.7558e-05  eta: 19:51:30  time: 0.6924  data_time: 0.0153  memory: 45143  top1_acc: 0.5000  top5_acc: 0.6250  loss_cls: 1.8503  loss: 1.8503
2022/08/01 22:01:50 - mmengine - INFO - Epoch(train) [4][1200/3757]  lr: 9.7558e-05  eta: 19:50:06  time: 0.6969  data_time: 0.0148  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.5500  loss: 1.5500
2022/08/01 22:03:00 - mmengine - INFO - Epoch(train) [4][1300/3757]  lr: 9.7558e-05  eta: 19:48:45  time: 0.7003  data_time: 0.0148  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 2.2804  loss: 2.2804
2022/08/01 22:04:10 - mmengine - INFO - Epoch(train) [4][1400/3757]  lr: 9.7558e-05  eta: 19:47:20  time: 0.6945  data_time: 0.0144  memory: 45143  top1_acc: 0.2500  top5_acc: 0.7500  loss_cls: 2.0099  loss: 2.0099
2022/08/01 22:05:20 - mmengine - INFO - Epoch(train) [4][1500/3757]  lr: 9.7558e-05  eta: 19:46:00  time: 0.7088  data_time: 0.0156  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.8460  loss: 1.8460
2022/08/01 22:06:29 - mmengine - INFO - Epoch(train) [4][1600/3757]  lr: 9.7558e-05  eta: 19:44:34  time: 0.6893  data_time: 0.0150  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 2.1127  loss: 2.1127
2022/08/01 22:07:38 - mmengine - INFO - Epoch(train) [4][1700/3757]  lr: 9.7558e-05  eta: 19:43:09  time: 0.6945  data_time: 0.0146  memory: 45143  top1_acc: 0.5000  top5_acc: 0.8750  loss_cls: 1.9544  loss: 1.9544
2022/08/01 22:07:58 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/01 22:08:48 - mmengine - INFO - Epoch(train) [4][1800/3757]  lr: 9.7558e-05  eta: 19:41:46  time: 0.6865  data_time: 0.0143  memory: 45143  top1_acc: 0.3750  top5_acc: 0.6250  loss_cls: 2.0788  loss: 2.0788
2022/08/01 22:09:58 - mmengine - INFO - Epoch(train) [4][1900/3757]  lr: 9.7558e-05  eta: 19:40:23  time: 0.6951  data_time: 0.0156  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 2.2441  loss: 2.2441
2022/08/01 22:11:07 - mmengine - INFO - Epoch(train) [4][2000/3757]  lr: 9.7558e-05  eta: 19:38:59  time: 0.6890  data_time: 0.0144  memory: 45143  top1_acc: 0.2500  top5_acc: 0.7500  loss_cls: 2.0046  loss: 2.0046
2022/08/01 22:12:17 - mmengine - INFO - Epoch(train) [4][2100/3757]  lr: 9.7558e-05  eta: 19:37:38  time: 0.7060  data_time: 0.0152  memory: 45143  top1_acc: 0.5000  top5_acc: 0.8750  loss_cls: 2.3151  loss: 2.3151
2022/08/01 22:13:26 - mmengine - INFO - Epoch(train) [4][2200/3757]  lr: 9.7558e-05  eta: 19:36:15  time: 0.6889  data_time: 0.0139  memory: 45143  top1_acc: 0.3750  top5_acc: 0.3750  loss_cls: 2.3643  loss: 2.3643
2022/08/01 22:14:36 - mmengine - INFO - Epoch(train) [4][2300/3757]  lr: 9.7558e-05  eta: 19:34:52  time: 0.6996  data_time: 0.0160  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.8845  loss: 1.8845
2022/08/01 22:15:46 - mmengine - INFO - Epoch(train) [4][2400/3757]  lr: 9.7558e-05  eta: 19:33:32  time: 0.6888  data_time: 0.0144  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 2.4291  loss: 2.4291
2022/08/01 22:16:55 - mmengine - INFO - Epoch(train) [4][2500/3757]  lr: 9.7558e-05  eta: 19:32:12  time: 0.6981  data_time: 0.0157  memory: 45143  top1_acc: 0.3750  top5_acc: 0.6250  loss_cls: 2.0166  loss: 2.0166
2022/08/01 22:18:05 - mmengine - INFO - Epoch(train) [4][2600/3757]  lr: 9.7558e-05  eta: 19:30:48  time: 0.6917  data_time: 0.0153  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.7120  loss: 1.7120
2022/08/01 22:19:14 - mmengine - INFO - Epoch(train) [4][2700/3757]  lr: 9.7558e-05  eta: 19:29:27  time: 0.6992  data_time: 0.0158  memory: 45143  top1_acc: 0.3750  top5_acc: 0.7500  loss_cls: 1.6035  loss: 1.6035
2022/08/01 22:19:35 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/01 22:20:24 - mmengine - INFO - Epoch(train) [4][2800/3757]  lr: 9.7558e-05  eta: 19:28:02  time: 0.6931  data_time: 0.0162  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.8391  loss: 1.8391
2022/08/01 22:21:34 - mmengine - INFO - Epoch(train) [4][2900/3757]  lr: 9.7558e-05  eta: 19:26:43  time: 0.6952  data_time: 0.0160  memory: 45143  top1_acc: 0.5000  top5_acc: 0.6250  loss_cls: 2.1566  loss: 2.1566
2022/08/01 22:22:43 - mmengine - INFO - Epoch(train) [4][3000/3757]  lr: 9.7558e-05  eta: 19:25:23  time: 0.6957  data_time: 0.0159  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 1.9338  loss: 1.9338
2022/08/01 22:23:53 - mmengine - INFO - Epoch(train) [4][3100/3757]  lr: 9.7558e-05  eta: 19:24:03  time: 0.7054  data_time: 0.0165  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.7644  loss: 1.7644
2022/08/01 22:25:02 - mmengine - INFO - Epoch(train) [4][3200/3757]  lr: 9.7558e-05  eta: 19:22:39  time: 0.6926  data_time: 0.0156  memory: 45143  top1_acc: 0.5000  top5_acc: 0.8750  loss_cls: 2.2024  loss: 2.2024
2022/08/01 22:26:11 - mmengine - INFO - Epoch(train) [4][3300/3757]  lr: 9.7558e-05  eta: 19:21:16  time: 0.6900  data_time: 0.0147  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 2.0567  loss: 2.0567
2022/08/01 22:27:21 - mmengine - INFO - Epoch(train) [4][3400/3757]  lr: 9.7558e-05  eta: 19:19:55  time: 0.6912  data_time: 0.0156  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 2.3088  loss: 2.3088
2022/08/01 22:28:30 - mmengine - INFO - Epoch(train) [4][3500/3757]  lr: 9.7558e-05  eta: 19:18:33  time: 0.6890  data_time: 0.0139  memory: 45143  top1_acc: 0.2500  top5_acc: 0.6250  loss_cls: 2.1418  loss: 2.1418
2022/08/01 22:29:39 - mmengine - INFO - Epoch(train) [4][3600/3757]  lr: 9.7558e-05  eta: 19:17:11  time: 0.6981  data_time: 0.0153  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 1.8178  loss: 1.8178
2022/08/01 22:30:49 - mmengine - INFO - Epoch(train) [4][3700/3757]  lr: 9.7558e-05  eta: 19:15:50  time: 0.6920  data_time: 0.0146  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.9777  loss: 1.9777
2022/08/01 22:31:09 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/01 22:31:28 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/01 22:31:28 - mmengine - INFO - Epoch(train) [4][3757/3757]  lr: 9.7558e-05  eta: 19:15:17  time: 0.6856  data_time: 0.0142  memory: 45143  top1_acc: 0.7143  top5_acc: 0.7143  loss_cls: 1.9535  loss: 1.9535
2022/08/01 22:32:40 - mmengine - INFO - Epoch(train) [5][100/3757]  lr: 9.5682e-05  eta: 19:12:38  time: 0.6909  data_time: 0.0148  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 1.8190  loss: 1.8190
2022/08/01 22:33:49 - mmengine - INFO - Epoch(train) [5][200/3757]  lr: 9.5682e-05  eta: 19:11:20  time: 0.6922  data_time: 0.0145  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 1.8600  loss: 1.8600
2022/08/01 22:34:59 - mmengine - INFO - Epoch(train) [5][300/3757]  lr: 9.5682e-05  eta: 19:10:02  time: 0.6904  data_time: 0.0151  memory: 45143  top1_acc: 0.5000  top5_acc: 0.8750  loss_cls: 1.5802  loss: 1.5802
2022/08/01 22:36:14 - mmengine - INFO - Epoch(train) [5][400/3757]  lr: 9.5682e-05  eta: 19:09:14  time: 0.9552  data_time: 0.0221  memory: 45143  top1_acc: 0.2500  top5_acc: 0.6250  loss_cls: 1.7459  loss: 1.7459
2022/08/01 22:37:23 - mmengine - INFO - Epoch(train) [5][500/3757]  lr: 9.5682e-05  eta: 19:07:56  time: 0.6975  data_time: 0.0161  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 2.0577  loss: 2.0577
2022/08/01 22:38:34 - mmengine - INFO - Epoch(train) [5][600/3757]  lr: 9.5682e-05  eta: 19:06:43  time: 0.6923  data_time: 0.0158  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 2.1273  loss: 2.1273
2022/08/01 22:39:44 - mmengine - INFO - Epoch(train) [5][700/3757]  lr: 9.5682e-05  eta: 19:05:25  time: 0.7010  data_time: 0.0159  memory: 45143  top1_acc: 0.6250  top5_acc: 1.0000  loss_cls: 1.6759  loss: 1.6759
2022/08/01 22:40:53 - mmengine - INFO - Epoch(train) [5][800/3757]  lr: 9.5682e-05  eta: 19:04:07  time: 0.6941  data_time: 0.0159  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 1.8496  loss: 1.8496
2022/08/01 22:42:03 - mmengine - INFO - Epoch(train) [5][900/3757]  lr: 9.5682e-05  eta: 19:02:48  time: 0.6974  data_time: 0.0147  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 2.2695  loss: 2.2695
2022/08/01 22:42:53 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/01 22:43:13 - mmengine - INFO - Epoch(train) [5][1000/3757]  lr: 9.5682e-05  eta: 19:01:31  time: 0.6895  data_time: 0.0137  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 2.0899  loss: 2.0899
2022/08/01 22:44:23 - mmengine - INFO - Epoch(train) [5][1100/3757]  lr: 9.5682e-05  eta: 19:00:14  time: 0.7076  data_time: 0.0164  memory: 45143  top1_acc: 0.3750  top5_acc: 0.8750  loss_cls: 1.8794  loss: 1.8794
2022/08/01 22:45:32 - mmengine - INFO - Epoch(train) [5][1200/3757]  lr: 9.5682e-05  eta: 18:58:55  time: 0.6893  data_time: 0.0140  memory: 45143  top1_acc: 0.3750  top5_acc: 0.6250  loss_cls: 2.0349  loss: 2.0349
2022/08/01 22:46:42 - mmengine - INFO - Epoch(train) [5][1300/3757]  lr: 9.5682e-05  eta: 18:57:38  time: 0.6949  data_time: 0.0155  memory: 45143  top1_acc: 0.3750  top5_acc: 0.7500  loss_cls: 1.9021  loss: 1.9021
2022/08/01 22:47:51 - mmengine - INFO - Epoch(train) [5][1400/3757]  lr: 9.5682e-05  eta: 18:56:20  time: 0.6907  data_time: 0.0144  memory: 45143  top1_acc: 0.3750  top5_acc: 0.6250  loss_cls: 1.8845  loss: 1.8845
2022/08/01 22:49:01 - mmengine - INFO - Epoch(train) [5][1500/3757]  lr: 9.5682e-05  eta: 18:55:02  time: 0.6953  data_time: 0.0158  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.9310  loss: 1.9310
2022/08/01 22:50:11 - mmengine - INFO - Epoch(train) [5][1600/3757]  lr: 9.5682e-05  eta: 18:53:44  time: 0.6894  data_time: 0.0148  memory: 45143  top1_acc: 0.3750  top5_acc: 0.6250  loss_cls: 1.9456  loss: 1.9456
2022/08/01 22:51:20 - mmengine - INFO - Epoch(train) [5][1700/3757]  lr: 9.5682e-05  eta: 18:52:24  time: 0.6917  data_time: 0.0155  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 1.6559  loss: 1.6559
2022/08/01 22:52:29 - mmengine - INFO - Epoch(train) [5][1800/3757]  lr: 9.5682e-05  eta: 18:51:05  time: 0.6883  data_time: 0.0139  memory: 45143  top1_acc: 0.3750  top5_acc: 0.6250  loss_cls: 1.7315  loss: 1.7315
2022/08/01 22:53:39 - mmengine - INFO - Epoch(train) [5][1900/3757]  lr: 9.5682e-05  eta: 18:49:48  time: 0.6959  data_time: 0.0153  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 1.6423  loss: 1.6423
2022/08/01 22:54:29 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/01 22:54:49 - mmengine - INFO - Epoch(train) [5][2000/3757]  lr: 9.5682e-05  eta: 18:48:31  time: 0.6939  data_time: 0.0164  memory: 45143  top1_acc: 0.5000  top5_acc: 0.6250  loss_cls: 1.4535  loss: 1.4535
2022/08/01 22:55:58 - mmengine - INFO - Epoch(train) [5][2100/3757]  lr: 9.5682e-05  eta: 18:47:12  time: 0.6911  data_time: 0.0156  memory: 45143  top1_acc: 0.5000  top5_acc: 0.8750  loss_cls: 2.1061  loss: 2.1061
2022/08/01 22:57:07 - mmengine - INFO - Epoch(train) [5][2200/3757]  lr: 9.5682e-05  eta: 18:45:52  time: 0.6939  data_time: 0.0158  memory: 45143  top1_acc: 0.6250  top5_acc: 0.6250  loss_cls: 1.8610  loss: 1.8610
2022/08/01 22:58:17 - mmengine - INFO - Epoch(train) [5][2300/3757]  lr: 9.5682e-05  eta: 18:44:36  time: 0.6938  data_time: 0.0148  memory: 45143  top1_acc: 0.3750  top5_acc: 0.8750  loss_cls: 1.8451  loss: 1.8451
2022/08/01 22:59:26 - mmengine - INFO - Epoch(train) [5][2400/3757]  lr: 9.5682e-05  eta: 18:43:16  time: 0.6916  data_time: 0.0155  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 1.8598  loss: 1.8598
2022/08/01 23:00:35 - mmengine - INFO - Epoch(train) [5][2500/3757]  lr: 9.5682e-05  eta: 18:41:59  time: 0.6951  data_time: 0.0145  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.7612  loss: 1.7612
2022/08/01 23:01:45 - mmengine - INFO - Epoch(train) [5][2600/3757]  lr: 9.5682e-05  eta: 18:40:42  time: 0.7018  data_time: 0.0155  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.7655  loss: 1.7655
2022/08/01 23:02:54 - mmengine - INFO - Epoch(train) [5][2700/3757]  lr: 9.5682e-05  eta: 18:39:24  time: 0.6898  data_time: 0.0144  memory: 45143  top1_acc: 0.6250  top5_acc: 1.0000  loss_cls: 1.7021  loss: 1.7021
2022/08/01 23:04:04 - mmengine - INFO - Epoch(train) [5][2800/3757]  lr: 9.5682e-05  eta: 18:38:07  time: 0.6917  data_time: 0.0151  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 1.7774  loss: 1.7774
2022/08/01 23:05:13 - mmengine - INFO - Epoch(train) [5][2900/3757]  lr: 9.5682e-05  eta: 18:36:50  time: 0.6895  data_time: 0.0140  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.7128  loss: 1.7128
2022/08/01 23:06:04 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/01 23:06:23 - mmengine - INFO - Epoch(train) [5][3000/3757]  lr: 9.5682e-05  eta: 18:35:35  time: 0.7002  data_time: 0.0160  memory: 45143  top1_acc: 0.6250  top5_acc: 1.0000  loss_cls: 1.9840  loss: 1.9840
2022/08/01 23:07:32 - mmengine - INFO - Epoch(train) [5][3100/3757]  lr: 9.5682e-05  eta: 18:34:17  time: 0.6881  data_time: 0.0138  memory: 45143  top1_acc: 0.3750  top5_acc: 0.6250  loss_cls: 1.8371  loss: 1.8371
2022/08/01 23:08:42 - mmengine - INFO - Epoch(train) [5][3200/3757]  lr: 9.5682e-05  eta: 18:32:59  time: 0.6940  data_time: 0.0162  memory: 45143  top1_acc: 0.5000  top5_acc: 0.5000  loss_cls: 1.8981  loss: 1.8981
2022/08/01 23:09:51 - mmengine - INFO - Epoch(train) [5][3300/3757]  lr: 9.5682e-05  eta: 18:31:42  time: 0.6889  data_time: 0.0143  memory: 45143  top1_acc: 0.5000  top5_acc: 0.5000  loss_cls: 1.9655  loss: 1.9655
2022/08/01 23:11:01 - mmengine - INFO - Epoch(train) [5][3400/3757]  lr: 9.5682e-05  eta: 18:30:24  time: 0.6912  data_time: 0.0144  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 2.0380  loss: 2.0380
2022/08/01 23:12:10 - mmengine - INFO - Epoch(train) [5][3500/3757]  lr: 9.5682e-05  eta: 18:29:06  time: 0.6912  data_time: 0.0156  memory: 45143  top1_acc: 0.3750  top5_acc: 0.6250  loss_cls: 2.0038  loss: 2.0038
2022/08/01 23:13:19 - mmengine - INFO - Epoch(train) [5][3600/3757]  lr: 9.5682e-05  eta: 18:27:49  time: 0.6959  data_time: 0.0167  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.9257  loss: 1.9257
2022/08/01 23:14:29 - mmengine - INFO - Epoch(train) [5][3700/3757]  lr: 9.5682e-05  eta: 18:26:35  time: 0.7006  data_time: 0.0159  memory: 45143  top1_acc: 0.1250  top5_acc: 0.2500  loss_cls: 2.0607  loss: 2.0607
2022/08/01 23:15:09 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/01 23:15:09 - mmengine - INFO - Epoch(train) [5][3757/3757]  lr: 9.5682e-05  eta: 18:26:06  time: 0.6960  data_time: 0.0165  memory: 45143  top1_acc: 0.8571  top5_acc: 1.0000  loss_cls: 2.0240  loss: 2.0240
2022/08/01 23:16:21 - mmengine - INFO - Epoch(train) [6][100/3757]  lr: 9.3306e-05  eta: 18:23:49  time: 0.6920  data_time: 0.0165  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 1.7037  loss: 1.7037
2022/08/01 23:17:31 - mmengine - INFO - Epoch(train) [6][200/3757]  lr: 9.3306e-05  eta: 18:22:35  time: 0.6988  data_time: 0.0166  memory: 45143  top1_acc: 0.5000  top5_acc: 0.8750  loss_cls: 1.5549  loss: 1.5549
2022/08/01 23:17:41 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/01 23:18:40 - mmengine - INFO - Epoch(train) [6][300/3757]  lr: 9.3306e-05  eta: 18:21:20  time: 0.6989  data_time: 0.0166  memory: 45143  top1_acc: 0.6250  top5_acc: 0.6250  loss_cls: 2.2897  loss: 2.2897
2022/08/01 23:19:50 - mmengine - INFO - Epoch(train) [6][400/3757]  lr: 9.3306e-05  eta: 18:20:04  time: 0.6943  data_time: 0.0169  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 1.6500  loss: 1.6500
2022/08/01 23:20:59 - mmengine - INFO - Epoch(train) [6][500/3757]  lr: 9.3306e-05  eta: 18:18:49  time: 0.7003  data_time: 0.0151  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.9052  loss: 1.9052
2022/08/01 23:22:09 - mmengine - INFO - Epoch(train) [6][600/3757]  lr: 9.3306e-05  eta: 18:17:34  time: 0.7012  data_time: 0.0158  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.7607  loss: 1.7607
2022/08/01 23:23:19 - mmengine - INFO - Epoch(train) [6][700/3757]  lr: 9.3306e-05  eta: 18:16:19  time: 0.7039  data_time: 0.0159  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.8378  loss: 1.8378
2022/08/01 23:24:29 - mmengine - INFO - Epoch(train) [6][800/3757]  lr: 9.3306e-05  eta: 18:15:06  time: 0.7043  data_time: 0.0163  memory: 45143  top1_acc: 0.3750  top5_acc: 0.6250  loss_cls: 1.8573  loss: 1.8573
2022/08/01 23:25:38 - mmengine - INFO - Epoch(train) [6][900/3757]  lr: 9.3306e-05  eta: 18:13:50  time: 0.6948  data_time: 0.0154  memory: 45143  top1_acc: 1.0000  top5_acc: 1.0000  loss_cls: 1.9905  loss: 1.9905
2022/08/01 23:26:48 - mmengine - INFO - Epoch(train) [6][1000/3757]  lr: 9.3306e-05  eta: 18:12:36  time: 0.6907  data_time: 0.0159  memory: 45143  top1_acc: 0.2500  top5_acc: 0.7500  loss_cls: 1.9611  loss: 1.9611
2022/08/01 23:27:57 - mmengine - INFO - Epoch(train) [6][1100/3757]  lr: 9.3306e-05  eta: 18:11:20  time: 0.6907  data_time: 0.0143  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.7055  loss: 1.7055
2022/08/01 23:29:07 - mmengine - INFO - Epoch(train) [6][1200/3757]  lr: 9.3306e-05  eta: 18:10:05  time: 0.6965  data_time: 0.0157  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.8768  loss: 1.8768
2022/08/01 23:29:17 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/01 23:30:18 - mmengine - INFO - Epoch(train) [6][1300/3757]  lr: 9.3306e-05  eta: 18:08:56  time: 0.6890  data_time: 0.0142  memory: 45143  top1_acc: 0.3750  top5_acc: 0.7500  loss_cls: 1.4933  loss: 1.4933
2022/08/01 23:31:27 - mmengine - INFO - Epoch(train) [6][1400/3757]  lr: 9.3306e-05  eta: 18:07:41  time: 0.7059  data_time: 0.0157  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.7577  loss: 1.7577
2022/08/01 23:32:37 - mmengine - INFO - Epoch(train) [6][1500/3757]  lr: 9.3306e-05  eta: 18:06:26  time: 0.6920  data_time: 0.0141  memory: 45143  top1_acc: 0.5000  top5_acc: 0.8750  loss_cls: 1.6982  loss: 1.6982
2022/08/01 23:33:47 - mmengine - INFO - Epoch(train) [6][1600/3757]  lr: 9.3306e-05  eta: 18:05:14  time: 0.6898  data_time: 0.0144  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.6902  loss: 1.6902
2022/08/01 23:34:56 - mmengine - INFO - Epoch(train) [6][1700/3757]  lr: 9.3306e-05  eta: 18:03:57  time: 0.6910  data_time: 0.0155  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.9506  loss: 1.9506
2022/08/01 23:36:06 - mmengine - INFO - Epoch(train) [6][1800/3757]  lr: 9.3306e-05  eta: 18:02:45  time: 0.6914  data_time: 0.0164  memory: 45143  top1_acc: 0.7500  top5_acc: 0.7500  loss_cls: 1.6295  loss: 1.6295
2022/08/01 23:37:15 - mmengine - INFO - Epoch(train) [6][1900/3757]  lr: 9.3306e-05  eta: 18:01:28  time: 0.6899  data_time: 0.0145  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 2.0115  loss: 2.0115
2022/08/01 23:38:26 - mmengine - INFO - Epoch(train) [6][2000/3757]  lr: 9.3306e-05  eta: 18:00:15  time: 0.6911  data_time: 0.0143  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.9248  loss: 1.9248
2022/08/01 23:39:35 - mmengine - INFO - Epoch(train) [6][2100/3757]  lr: 9.3306e-05  eta: 17:59:02  time: 0.6937  data_time: 0.0161  memory: 45143  top1_acc: 0.7500  top5_acc: 0.7500  loss_cls: 1.7594  loss: 1.7594
2022/08/01 23:40:45 - mmengine - INFO - Epoch(train) [6][2200/3757]  lr: 9.3306e-05  eta: 17:57:48  time: 0.6877  data_time: 0.0148  memory: 45143  top1_acc: 0.5000  top5_acc: 0.6250  loss_cls: 1.6474  loss: 1.6474
2022/08/01 23:40:56 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/01 23:41:55 - mmengine - INFO - Epoch(train) [6][2300/3757]  lr: 9.3306e-05  eta: 17:56:35  time: 0.7078  data_time: 0.0173  memory: 45143  top1_acc: 0.3750  top5_acc: 0.8750  loss_cls: 1.7131  loss: 1.7131
2022/08/01 23:43:04 - mmengine - INFO - Epoch(train) [6][2400/3757]  lr: 9.3306e-05  eta: 17:55:19  time: 0.6897  data_time: 0.0152  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 2.0044  loss: 2.0044
2022/08/01 23:44:14 - mmengine - INFO - Epoch(train) [6][2500/3757]  lr: 9.3306e-05  eta: 17:54:05  time: 0.6907  data_time: 0.0155  memory: 45143  top1_acc: 0.5000  top5_acc: 0.8750  loss_cls: 2.1138  loss: 2.1138
2022/08/01 23:45:23 - mmengine - INFO - Epoch(train) [6][2600/3757]  lr: 9.3306e-05  eta: 17:52:50  time: 0.6909  data_time: 0.0157  memory: 45143  top1_acc: 0.1250  top5_acc: 1.0000  loss_cls: 1.9084  loss: 1.9084
2022/08/01 23:46:33 - mmengine - INFO - Epoch(train) [6][2700/3757]  lr: 9.3306e-05  eta: 17:51:35  time: 0.7062  data_time: 0.0171  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 2.0144  loss: 2.0144
2022/08/01 23:47:42 - mmengine - INFO - Epoch(train) [6][2800/3757]  lr: 9.3306e-05  eta: 17:50:20  time: 0.6943  data_time: 0.0159  memory: 45143  top1_acc: 0.6250  top5_acc: 1.0000  loss_cls: 1.9138  loss: 1.9138
2022/08/01 23:48:52 - mmengine - INFO - Epoch(train) [6][2900/3757]  lr: 9.3306e-05  eta: 17:49:08  time: 0.6996  data_time: 0.0156  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.7148  loss: 1.7148
2022/08/01 23:50:02 - mmengine - INFO - Epoch(train) [6][3000/3757]  lr: 9.3306e-05  eta: 17:47:55  time: 0.6926  data_time: 0.0160  memory: 45143  top1_acc: 0.5000  top5_acc: 0.8750  loss_cls: 1.8264  loss: 1.8264
2022/08/01 23:51:12 - mmengine - INFO - Epoch(train) [6][3100/3757]  lr: 9.3306e-05  eta: 17:46:40  time: 0.6943  data_time: 0.0159  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 2.0025  loss: 2.0025
2022/08/01 23:52:22 - mmengine - INFO - Epoch(train) [6][3200/3757]  lr: 9.3306e-05  eta: 17:45:28  time: 0.7023  data_time: 0.0157  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.9488  loss: 1.9488
2022/08/01 23:52:32 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/01 23:53:31 - mmengine - INFO - Epoch(train) [6][3300/3757]  lr: 9.3306e-05  eta: 17:44:12  time: 0.6982  data_time: 0.0153  memory: 45143  top1_acc: 0.5000  top5_acc: 0.6250  loss_cls: 1.9458  loss: 1.9458
2022/08/01 23:54:41 - mmengine - INFO - Epoch(train) [6][3400/3757]  lr: 9.3306e-05  eta: 17:42:58  time: 0.6867  data_time: 0.0147  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 1.7222  loss: 1.7222
2022/08/01 23:55:50 - mmengine - INFO - Epoch(train) [6][3500/3757]  lr: 9.3306e-05  eta: 17:41:43  time: 0.6982  data_time: 0.0159  memory: 45143  top1_acc: 0.3750  top5_acc: 0.5000  loss_cls: 1.9187  loss: 1.9187
2022/08/01 23:57:00 - mmengine - INFO - Epoch(train) [6][3600/3757]  lr: 9.3306e-05  eta: 17:40:31  time: 0.6904  data_time: 0.0155  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 1.8338  loss: 1.8338
2022/08/01 23:58:10 - mmengine - INFO - Epoch(train) [6][3700/3757]  lr: 9.3306e-05  eta: 17:39:18  time: 0.7098  data_time: 0.0164  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 1.7445  loss: 1.7445
2022/08/01 23:58:50 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/01 23:58:50 - mmengine - INFO - Epoch(train) [6][3757/3757]  lr: 9.3306e-05  eta: 17:38:49  time: 0.7214  data_time: 0.0181  memory: 45143  top1_acc: 0.5714  top5_acc: 1.0000  loss_cls: 1.8401  loss: 1.8401
2022/08/01 23:58:50 - mmengine - INFO - Saving checkpoint at 6 epochs
2022/08/01 23:59:27 - mmengine - INFO - Epoch(val) [6][100/310]    eta: 0:00:57  time: 0.2722  data_time: 0.0120  memory: 8742  
2022/08/01 23:59:55 - mmengine - INFO - Epoch(val) [6][200/310]    eta: 0:00:32  time: 0.2915  data_time: 0.0124  memory: 8742  
2022/08/02 00:00:24 - mmengine - INFO - Epoch(val) [6][300/310]    eta: 0:00:02  time: 0.2630  data_time: 0.0101  memory: 8742  
2022/08/02 00:00:27 - mmengine - INFO - Epoch(val) [6][310/310]  acc/top1: 0.6557  acc/top5: 0.8711  acc/mean1: 0.6555
2022/08/02 00:00:27 - mmengine - INFO - The previous best checkpoint /mnt/lustre/daiwenxun/X/mmaction2/work_dirs/swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb/best_acc/top1_epoch_4.pth is removed
2022/08/02 00:00:31 - mmengine - INFO - The best checkpoint with 0.6557 acc/top1 at 7 epoch is saved to best_acc/top1_epoch_7.pth.
2022/08/02 00:01:42 - mmengine - INFO - Epoch(train) [7][100/3757]  lr: 9.0455e-05  eta: 17:36:41  time: 0.7051  data_time: 0.0163  memory: 45143  top1_acc: 0.5000  top5_acc: 0.8750  loss_cls: 1.7336  loss: 1.7336
2022/08/02 00:02:52 - mmengine - INFO - Epoch(train) [7][200/3757]  lr: 9.0455e-05  eta: 17:35:27  time: 0.6987  data_time: 0.0167  memory: 45143  top1_acc: 0.5000  top5_acc: 0.6250  loss_cls: 1.7771  loss: 1.7771
2022/08/02 00:04:01 - mmengine - INFO - Epoch(train) [7][300/3757]  lr: 9.0455e-05  eta: 17:34:14  time: 0.6925  data_time: 0.0145  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 1.3893  loss: 1.3893
2022/08/02 00:05:11 - mmengine - INFO - Epoch(train) [7][400/3757]  lr: 9.0455e-05  eta: 17:32:59  time: 0.6958  data_time: 0.0155  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.2862  loss: 1.2862
2022/08/02 00:05:51 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 00:06:21 - mmengine - INFO - Epoch(train) [7][500/3757]  lr: 9.0455e-05  eta: 17:31:47  time: 0.6968  data_time: 0.0150  memory: 45143  top1_acc: 0.5000  top5_acc: 0.8750  loss_cls: 2.0572  loss: 2.0572
2022/08/02 00:07:31 - mmengine - INFO - Epoch(train) [7][600/3757]  lr: 9.0455e-05  eta: 17:30:35  time: 0.6908  data_time: 0.0146  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.9014  loss: 1.9014
2022/08/02 00:08:40 - mmengine - INFO - Epoch(train) [7][700/3757]  lr: 9.0455e-05  eta: 17:29:23  time: 0.6986  data_time: 0.0149  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.9345  loss: 1.9345
2022/08/02 00:09:50 - mmengine - INFO - Epoch(train) [7][800/3757]  lr: 9.0455e-05  eta: 17:28:10  time: 0.6921  data_time: 0.0154  memory: 45143  top1_acc: 0.3750  top5_acc: 0.6250  loss_cls: 1.8720  loss: 1.8720
2022/08/02 00:11:00 - mmengine - INFO - Epoch(train) [7][900/3757]  lr: 9.0455e-05  eta: 17:26:56  time: 0.6931  data_time: 0.0172  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 1.5003  loss: 1.5003
2022/08/02 00:12:09 - mmengine - INFO - Epoch(train) [7][1000/3757]  lr: 9.0455e-05  eta: 17:25:43  time: 0.6910  data_time: 0.0154  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.8048  loss: 1.8048
2022/08/02 00:13:19 - mmengine - INFO - Epoch(train) [7][1100/3757]  lr: 9.0455e-05  eta: 17:24:29  time: 0.6907  data_time: 0.0143  memory: 45143  top1_acc: 0.5000  top5_acc: 0.6250  loss_cls: 1.5493  loss: 1.5493
2022/08/02 00:14:28 - mmengine - INFO - Epoch(train) [7][1200/3757]  lr: 9.0455e-05  eta: 17:23:16  time: 0.7017  data_time: 0.0167  memory: 45143  top1_acc: 0.5000  top5_acc: 0.6250  loss_cls: 1.8197  loss: 1.8197
2022/08/02 00:15:38 - mmengine - INFO - Epoch(train) [7][1300/3757]  lr: 9.0455e-05  eta: 17:22:02  time: 0.6948  data_time: 0.0150  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.7567  loss: 1.7567
2022/08/02 00:16:47 - mmengine - INFO - Epoch(train) [7][1400/3757]  lr: 9.0455e-05  eta: 17:20:49  time: 0.6949  data_time: 0.0165  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.6761  loss: 1.6761
2022/08/02 00:17:28 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 00:17:57 - mmengine - INFO - Epoch(train) [7][1500/3757]  lr: 9.0455e-05  eta: 17:19:37  time: 0.6922  data_time: 0.0144  memory: 45143  top1_acc: 1.0000  top5_acc: 1.0000  loss_cls: 1.6488  loss: 1.6488
2022/08/02 00:19:07 - mmengine - INFO - Epoch(train) [7][1600/3757]  lr: 9.0455e-05  eta: 17:18:23  time: 0.6998  data_time: 0.0158  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.8962  loss: 1.8962
2022/08/02 00:20:16 - mmengine - INFO - Epoch(train) [7][1700/3757]  lr: 9.0455e-05  eta: 17:17:10  time: 0.7054  data_time: 0.0162  memory: 45143  top1_acc: 1.0000  top5_acc: 1.0000  loss_cls: 1.7542  loss: 1.7542
2022/08/02 00:21:26 - mmengine - INFO - Epoch(train) [7][1800/3757]  lr: 9.0455e-05  eta: 17:15:57  time: 0.7052  data_time: 0.0175  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.7455  loss: 1.7455
2022/08/02 00:22:36 - mmengine - INFO - Epoch(train) [7][1900/3757]  lr: 9.0455e-05  eta: 17:14:45  time: 0.7000  data_time: 0.0168  memory: 45143  top1_acc: 0.7500  top5_acc: 0.7500  loss_cls: 1.5199  loss: 1.5199
2022/08/02 00:23:45 - mmengine - INFO - Epoch(train) [7][2000/3757]  lr: 9.0455e-05  eta: 17:13:32  time: 0.6984  data_time: 0.0179  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 1.9808  loss: 1.9808
2022/08/02 00:24:55 - mmengine - INFO - Epoch(train) [7][2100/3757]  lr: 9.0455e-05  eta: 17:12:19  time: 0.6934  data_time: 0.0168  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.5748  loss: 1.5748
2022/08/02 00:26:04 - mmengine - INFO - Epoch(train) [7][2200/3757]  lr: 9.0455e-05  eta: 17:11:05  time: 0.6915  data_time: 0.0163  memory: 45143  top1_acc: 0.6250  top5_acc: 0.6250  loss_cls: 1.9778  loss: 1.9778
2022/08/02 00:27:14 - mmengine - INFO - Epoch(train) [7][2300/3757]  lr: 9.0455e-05  eta: 17:09:51  time: 0.6911  data_time: 0.0157  memory: 45143  top1_acc: 0.2500  top5_acc: 0.5000  loss_cls: 1.7316  loss: 1.7316
2022/08/02 00:28:24 - mmengine - INFO - Epoch(train) [7][2400/3757]  lr: 9.0455e-05  eta: 17:08:39  time: 0.6938  data_time: 0.0158  memory: 45143  top1_acc: 0.3750  top5_acc: 0.6250  loss_cls: 2.2136  loss: 2.2136
2022/08/02 00:29:04 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 00:29:34 - mmengine - INFO - Epoch(train) [7][2500/3757]  lr: 9.0455e-05  eta: 17:07:29  time: 0.7063  data_time: 0.0146  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.8418  loss: 1.8418
2022/08/02 00:30:43 - mmengine - INFO - Epoch(train) [7][2600/3757]  lr: 9.0455e-05  eta: 17:06:15  time: 0.6921  data_time: 0.0160  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 1.6798  loss: 1.6798
2022/08/02 00:31:53 - mmengine - INFO - Epoch(train) [7][2700/3757]  lr: 9.0455e-05  eta: 17:05:02  time: 0.6898  data_time: 0.0144  memory: 45143  top1_acc: 0.3750  top5_acc: 0.7500  loss_cls: 1.6967  loss: 1.6967
2022/08/02 00:33:02 - mmengine - INFO - Epoch(train) [7][2800/3757]  lr: 9.0455e-05  eta: 17:03:49  time: 0.6931  data_time: 0.0159  memory: 45143  top1_acc: 0.6250  top5_acc: 0.6250  loss_cls: 1.7201  loss: 1.7201
2022/08/02 00:34:12 - mmengine - INFO - Epoch(train) [7][2900/3757]  lr: 9.0455e-05  eta: 17:02:38  time: 0.7050  data_time: 0.0155  memory: 45143  top1_acc: 0.5000  top5_acc: 0.8750  loss_cls: 1.7054  loss: 1.7054
2022/08/02 00:35:23 - mmengine - INFO - Epoch(train) [7][3000/3757]  lr: 9.0455e-05  eta: 17:01:27  time: 0.6935  data_time: 0.0158  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.8488  loss: 1.8488
2022/08/02 00:36:32 - mmengine - INFO - Epoch(train) [7][3100/3757]  lr: 9.0455e-05  eta: 17:00:15  time: 0.6940  data_time: 0.0140  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.5665  loss: 1.5665
2022/08/02 00:37:42 - mmengine - INFO - Epoch(train) [7][3200/3757]  lr: 9.0455e-05  eta: 16:59:03  time: 0.6947  data_time: 0.0161  memory: 45143  top1_acc: 1.0000  top5_acc: 1.0000  loss_cls: 1.9160  loss: 1.9160
2022/08/02 00:38:52 - mmengine - INFO - Epoch(train) [7][3300/3757]  lr: 9.0455e-05  eta: 16:57:52  time: 0.6917  data_time: 0.0154  memory: 45143  top1_acc: 0.3750  top5_acc: 0.8750  loss_cls: 1.8316  loss: 1.8316
2022/08/02 00:40:02 - mmengine - INFO - Epoch(train) [7][3400/3757]  lr: 9.0455e-05  eta: 16:56:40  time: 0.6900  data_time: 0.0148  memory: 45143  top1_acc: 0.5000  top5_acc: 0.6250  loss_cls: 1.7171  loss: 1.7171
2022/08/02 00:40:43 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 00:41:12 - mmengine - INFO - Epoch(train) [7][3500/3757]  lr: 9.0455e-05  eta: 16:55:29  time: 0.7023  data_time: 0.0155  memory: 45143  top1_acc: 0.3750  top5_acc: 0.8750  loss_cls: 1.6552  loss: 1.6552
2022/08/02 00:42:22 - mmengine - INFO - Epoch(train) [7][3600/3757]  lr: 9.0455e-05  eta: 16:54:18  time: 0.6911  data_time: 0.0155  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 2.0208  loss: 2.0208
2022/08/02 00:43:32 - mmengine - INFO - Epoch(train) [7][3700/3757]  lr: 9.0455e-05  eta: 16:53:05  time: 0.6916  data_time: 0.0159  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.6400  loss: 1.6400
2022/08/02 00:44:11 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 00:44:11 - mmengine - INFO - Epoch(train) [7][3757/3757]  lr: 9.0455e-05  eta: 16:52:37  time: 0.6822  data_time: 0.0157  memory: 45143  top1_acc: 0.5714  top5_acc: 0.7143  loss_cls: 1.6821  loss: 1.6821
2022/08/02 00:45:23 - mmengine - INFO - Epoch(train) [8][100/3757]  lr: 8.7161e-05  eta: 16:50:38  time: 0.6911  data_time: 0.0156  memory: 45143  top1_acc: 0.7500  top5_acc: 0.7500  loss_cls: 1.5662  loss: 1.5662
2022/08/02 00:46:32 - mmengine - INFO - Epoch(train) [8][200/3757]  lr: 8.7161e-05  eta: 16:49:25  time: 0.6906  data_time: 0.0153  memory: 45143  top1_acc: 0.3750  top5_acc: 0.8750  loss_cls: 1.8645  loss: 1.8645
2022/08/02 00:47:42 - mmengine - INFO - Epoch(train) [8][300/3757]  lr: 8.7161e-05  eta: 16:48:14  time: 0.6925  data_time: 0.0143  memory: 45143  top1_acc: 0.3750  top5_acc: 0.8750  loss_cls: 1.5812  loss: 1.5812
2022/08/02 00:48:51 - mmengine - INFO - Epoch(train) [8][400/3757]  lr: 8.7161e-05  eta: 16:47:01  time: 0.6914  data_time: 0.0158  memory: 45143  top1_acc: 0.3750  top5_acc: 0.7500  loss_cls: 1.6144  loss: 1.6144
2022/08/02 00:50:01 - mmengine - INFO - Epoch(train) [8][500/3757]  lr: 8.7161e-05  eta: 16:45:48  time: 0.6908  data_time: 0.0150  memory: 45143  top1_acc: 0.3750  top5_acc: 1.0000  loss_cls: 1.8082  loss: 1.8082
2022/08/02 00:51:11 - mmengine - INFO - Epoch(train) [8][600/3757]  lr: 8.7161e-05  eta: 16:44:36  time: 0.6930  data_time: 0.0161  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.6298  loss: 1.6298
2022/08/02 00:52:20 - mmengine - INFO - Epoch(train) [8][700/3757]  lr: 8.7161e-05  eta: 16:43:23  time: 0.6935  data_time: 0.0161  memory: 45143  top1_acc: 0.5000  top5_acc: 0.8750  loss_cls: 1.7293  loss: 1.7293
2022/08/02 00:52:21 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 00:53:29 - mmengine - INFO - Epoch(train) [8][800/3757]  lr: 8.7161e-05  eta: 16:42:10  time: 0.6925  data_time: 0.0165  memory: 45143  top1_acc: 0.5000  top5_acc: 0.6250  loss_cls: 1.7746  loss: 1.7746
2022/08/02 00:54:39 - mmengine - INFO - Epoch(train) [8][900/3757]  lr: 8.7161e-05  eta: 16:40:58  time: 0.7059  data_time: 0.0164  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 1.9966  loss: 1.9966
2022/08/02 00:55:49 - mmengine - INFO - Epoch(train) [8][1000/3757]  lr: 8.7161e-05  eta: 16:39:47  time: 0.7015  data_time: 0.0159  memory: 45143  top1_acc: 0.3750  top5_acc: 0.7500  loss_cls: 1.7212  loss: 1.7212
2022/08/02 00:56:59 - mmengine - INFO - Epoch(train) [8][1100/3757]  lr: 8.7161e-05  eta: 16:38:35  time: 0.7026  data_time: 0.0158  memory: 45143  top1_acc: 0.3750  top5_acc: 0.6250  loss_cls: 1.6660  loss: 1.6660
2022/08/02 00:58:08 - mmengine - INFO - Epoch(train) [8][1200/3757]  lr: 8.7161e-05  eta: 16:37:21  time: 0.6924  data_time: 0.0155  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 1.7133  loss: 1.7133
2022/08/02 00:59:18 - mmengine - INFO - Epoch(train) [8][1300/3757]  lr: 8.7161e-05  eta: 16:36:11  time: 0.7198  data_time: 0.0163  memory: 45143  top1_acc: 0.6250  top5_acc: 1.0000  loss_cls: 1.8198  loss: 1.8198
2022/08/02 01:00:27 - mmengine - INFO - Epoch(train) [8][1400/3757]  lr: 8.7161e-05  eta: 16:34:58  time: 0.6986  data_time: 0.0169  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.7096  loss: 1.7096
2022/08/02 01:01:37 - mmengine - INFO - Epoch(train) [8][1500/3757]  lr: 8.7161e-05  eta: 16:33:47  time: 0.7075  data_time: 0.0151  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.4159  loss: 1.4159
2022/08/02 01:02:47 - mmengine - INFO - Epoch(train) [8][1600/3757]  lr: 8.7161e-05  eta: 16:32:34  time: 0.6946  data_time: 0.0149  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.6407  loss: 1.6407
2022/08/02 01:03:57 - mmengine - INFO - Epoch(train) [8][1700/3757]  lr: 8.7161e-05  eta: 16:31:24  time: 0.7004  data_time: 0.0156  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.9482  loss: 1.9482
2022/08/02 01:03:58 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 01:05:07 - mmengine - INFO - Epoch(train) [8][1800/3757]  lr: 8.7161e-05  eta: 16:30:13  time: 0.6915  data_time: 0.0161  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.8242  loss: 1.8242
2022/08/02 01:06:16 - mmengine - INFO - Epoch(train) [8][1900/3757]  lr: 8.7161e-05  eta: 16:29:00  time: 0.6906  data_time: 0.0152  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 1.6069  loss: 1.6069
2022/08/02 01:07:26 - mmengine - INFO - Epoch(train) [8][2000/3757]  lr: 8.7161e-05  eta: 16:27:49  time: 0.6999  data_time: 0.0182  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.8330  loss: 1.8330
2022/08/02 01:08:36 - mmengine - INFO - Epoch(train) [8][2100/3757]  lr: 8.7161e-05  eta: 16:26:36  time: 0.6916  data_time: 0.0146  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.5796  loss: 1.5796
2022/08/02 01:09:46 - mmengine - INFO - Epoch(train) [8][2200/3757]  lr: 8.7161e-05  eta: 16:25:25  time: 0.7062  data_time: 0.0160  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.7921  loss: 1.7921
2022/08/02 01:10:56 - mmengine - INFO - Epoch(train) [8][2300/3757]  lr: 8.7161e-05  eta: 16:24:15  time: 0.6932  data_time: 0.0149  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.7396  loss: 1.7396
2022/08/02 01:12:06 - mmengine - INFO - Epoch(train) [8][2400/3757]  lr: 8.7161e-05  eta: 16:23:04  time: 0.6967  data_time: 0.0163  memory: 45143  top1_acc: 0.3750  top5_acc: 0.7500  loss_cls: 1.6192  loss: 1.6192
2022/08/02 01:13:15 - mmengine - INFO - Epoch(train) [8][2500/3757]  lr: 8.7161e-05  eta: 16:21:52  time: 0.6896  data_time: 0.0143  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.4785  loss: 1.4785
2022/08/02 01:14:25 - mmengine - INFO - Epoch(train) [8][2600/3757]  lr: 8.7161e-05  eta: 16:20:40  time: 0.6910  data_time: 0.0163  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.5593  loss: 1.5593
2022/08/02 01:15:35 - mmengine - INFO - Epoch(train) [8][2700/3757]  lr: 8.7161e-05  eta: 16:19:28  time: 0.6894  data_time: 0.0147  memory: 45143  top1_acc: 0.7500  top5_acc: 0.7500  loss_cls: 1.6647  loss: 1.6647
2022/08/02 01:15:35 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 01:16:44 - mmengine - INFO - Epoch(train) [8][2800/3757]  lr: 8.7161e-05  eta: 16:18:15  time: 0.6967  data_time: 0.0151  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 1.5809  loss: 1.5809
2022/08/02 01:17:54 - mmengine - INFO - Epoch(train) [8][2900/3757]  lr: 8.7161e-05  eta: 16:17:04  time: 0.6920  data_time: 0.0149  memory: 45143  top1_acc: 0.5000  top5_acc: 0.6250  loss_cls: 1.6382  loss: 1.6382
2022/08/02 01:19:03 - mmengine - INFO - Epoch(train) [8][3000/3757]  lr: 8.7161e-05  eta: 16:15:52  time: 0.6935  data_time: 0.0151  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 1.6155  loss: 1.6155
2022/08/02 01:20:13 - mmengine - INFO - Epoch(train) [8][3100/3757]  lr: 8.7161e-05  eta: 16:14:41  time: 0.6923  data_time: 0.0165  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 1.6001  loss: 1.6001
2022/08/02 01:21:23 - mmengine - INFO - Epoch(train) [8][3200/3757]  lr: 8.7161e-05  eta: 16:13:29  time: 0.6957  data_time: 0.0169  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 1.6812  loss: 1.6812
2022/08/02 01:22:33 - mmengine - INFO - Epoch(train) [8][3300/3757]  lr: 8.7161e-05  eta: 16:12:18  time: 0.7080  data_time: 0.0170  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.7419  loss: 1.7419
2022/08/02 01:23:42 - mmengine - INFO - Epoch(train) [8][3400/3757]  lr: 8.7161e-05  eta: 16:11:06  time: 0.6985  data_time: 0.0155  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.6763  loss: 1.6763
2022/08/02 01:24:52 - mmengine - INFO - Epoch(train) [8][3500/3757]  lr: 8.7161e-05  eta: 16:09:54  time: 0.6929  data_time: 0.0163  memory: 45143  top1_acc: 0.7500  top5_acc: 0.7500  loss_cls: 1.6679  loss: 1.6679
2022/08/02 01:26:02 - mmengine - INFO - Epoch(train) [8][3600/3757]  lr: 8.7161e-05  eta: 16:08:43  time: 0.7003  data_time: 0.0159  memory: 45143  top1_acc: 0.6250  top5_acc: 1.0000  loss_cls: 1.6991  loss: 1.6991
2022/08/02 01:27:11 - mmengine - INFO - Epoch(train) [8][3700/3757]  lr: 8.7161e-05  eta: 16:07:30  time: 0.6952  data_time: 0.0166  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 1.8128  loss: 1.8128
2022/08/02 01:27:12 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 01:27:51 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 01:27:51 - mmengine - INFO - Epoch(train) [8][3757/3757]  lr: 8.7161e-05  eta: 16:07:02  time: 0.6905  data_time: 0.0192  memory: 45143  top1_acc: 1.0000  top5_acc: 1.0000  loss_cls: 1.8136  loss: 1.8136
2022/08/02 01:29:03 - mmengine - INFO - Epoch(train) [9][100/3757]  lr: 8.3461e-05  eta: 16:05:14  time: 0.6964  data_time: 0.0163  memory: 45143  top1_acc: 0.7500  top5_acc: 0.7500  loss_cls: 1.7144  loss: 1.7144
2022/08/02 01:30:13 - mmengine - INFO - Epoch(train) [9][200/3757]  lr: 8.3461e-05  eta: 16:04:02  time: 0.6951  data_time: 0.0157  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.6644  loss: 1.6644
2022/08/02 01:31:22 - mmengine - INFO - Epoch(train) [9][300/3757]  lr: 8.3461e-05  eta: 16:02:50  time: 0.6944  data_time: 0.0173  memory: 45143  top1_acc: 0.3750  top5_acc: 0.6250  loss_cls: 1.4991  loss: 1.4991
2022/08/02 01:32:32 - mmengine - INFO - Epoch(train) [9][400/3757]  lr: 8.3461e-05  eta: 16:01:38  time: 0.7053  data_time: 0.0176  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 1.6969  loss: 1.6969
2022/08/02 01:33:42 - mmengine - INFO - Epoch(train) [9][500/3757]  lr: 8.3461e-05  eta: 16:00:26  time: 0.6925  data_time: 0.0171  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.3489  loss: 1.3489
2022/08/02 01:34:51 - mmengine - INFO - Epoch(train) [9][600/3757]  lr: 8.3461e-05  eta: 15:59:15  time: 0.7076  data_time: 0.0166  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 1.8069  loss: 1.8069
2022/08/02 01:36:02 - mmengine - INFO - Epoch(train) [9][700/3757]  lr: 8.3461e-05  eta: 15:58:05  time: 0.7062  data_time: 0.0159  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 1.7185  loss: 1.7185
2022/08/02 01:37:12 - mmengine - INFO - Epoch(train) [9][800/3757]  lr: 8.3461e-05  eta: 15:56:55  time: 0.6970  data_time: 0.0167  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.5026  loss: 1.5026
2022/08/02 01:38:22 - mmengine - INFO - Epoch(train) [9][900/3757]  lr: 8.3461e-05  eta: 15:55:44  time: 0.7164  data_time: 0.0175  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.4685  loss: 1.4685
2022/08/02 01:38:52 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 01:39:31 - mmengine - INFO - Epoch(train) [9][1000/3757]  lr: 8.3461e-05  eta: 15:54:32  time: 0.7032  data_time: 0.0151  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.8140  loss: 1.8140
2022/08/02 01:40:41 - mmengine - INFO - Epoch(train) [9][1100/3757]  lr: 8.3461e-05  eta: 15:53:20  time: 0.6969  data_time: 0.0162  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.9658  loss: 1.9658
2022/08/02 01:41:50 - mmengine - INFO - Epoch(train) [9][1200/3757]  lr: 8.3461e-05  eta: 15:52:09  time: 0.6905  data_time: 0.0153  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.5773  loss: 1.5773
2022/08/02 01:43:00 - mmengine - INFO - Epoch(train) [9][1300/3757]  lr: 8.3461e-05  eta: 15:50:57  time: 0.6914  data_time: 0.0155  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.4898  loss: 1.4898
2022/08/02 01:44:09 - mmengine - INFO - Epoch(train) [9][1400/3757]  lr: 8.3461e-05  eta: 15:49:45  time: 0.6908  data_time: 0.0153  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.6251  loss: 1.6251
2022/08/02 01:45:19 - mmengine - INFO - Epoch(train) [9][1500/3757]  lr: 8.3461e-05  eta: 15:48:34  time: 0.6931  data_time: 0.0156  memory: 45143  top1_acc: 0.5000  top5_acc: 0.8750  loss_cls: 1.6453  loss: 1.6453
2022/08/02 01:46:29 - mmengine - INFO - Epoch(train) [9][1600/3757]  lr: 8.3461e-05  eta: 15:47:24  time: 0.6953  data_time: 0.0155  memory: 45143  top1_acc: 1.0000  top5_acc: 1.0000  loss_cls: 1.4056  loss: 1.4056
2022/08/02 01:47:40 - mmengine - INFO - Epoch(train) [9][1700/3757]  lr: 8.3461e-05  eta: 15:46:15  time: 0.7116  data_time: 0.0203  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.6332  loss: 1.6332
2022/08/02 01:48:49 - mmengine - INFO - Epoch(train) [9][1800/3757]  lr: 8.3461e-05  eta: 15:45:04  time: 0.6959  data_time: 0.0164  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.6248  loss: 1.6248
2022/08/02 01:49:59 - mmengine - INFO - Epoch(train) [9][1900/3757]  lr: 8.3461e-05  eta: 15:43:53  time: 0.6982  data_time: 0.0157  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 1.4014  loss: 1.4014
2022/08/02 01:50:30 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 01:51:09 - mmengine - INFO - Epoch(train) [9][2000/3757]  lr: 8.3461e-05  eta: 15:42:43  time: 0.6915  data_time: 0.0153  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 1.7123  loss: 1.7123
2022/08/02 01:52:19 - mmengine - INFO - Epoch(train) [9][2100/3757]  lr: 8.3461e-05  eta: 15:41:31  time: 0.6908  data_time: 0.0159  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 1.4749  loss: 1.4749
2022/08/02 01:53:29 - mmengine - INFO - Epoch(train) [9][2200/3757]  lr: 8.3461e-05  eta: 15:40:21  time: 0.6964  data_time: 0.0146  memory: 45143  top1_acc: 0.6250  top5_acc: 0.6250  loss_cls: 1.6036  loss: 1.6036
2022/08/02 01:54:39 - mmengine - INFO - Epoch(train) [9][2300/3757]  lr: 8.3461e-05  eta: 15:39:09  time: 0.6989  data_time: 0.0160  memory: 45143  top1_acc: 0.5000  top5_acc: 0.5000  loss_cls: 1.7081  loss: 1.7081
2022/08/02 01:55:49 - mmengine - INFO - Epoch(train) [9][2400/3757]  lr: 8.3461e-05  eta: 15:37:59  time: 0.6948  data_time: 0.0152  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.5804  loss: 1.5804
2022/08/02 01:57:00 - mmengine - INFO - Epoch(train) [9][2500/3757]  lr: 8.3461e-05  eta: 15:36:51  time: 0.7108  data_time: 0.0154  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.4984  loss: 1.4984
2022/08/02 01:58:10 - mmengine - INFO - Epoch(train) [9][2600/3757]  lr: 8.3461e-05  eta: 15:35:41  time: 0.6949  data_time: 0.0146  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 1.6343  loss: 1.6343
2022/08/02 01:59:20 - mmengine - INFO - Epoch(train) [9][2700/3757]  lr: 8.3461e-05  eta: 15:34:31  time: 0.7030  data_time: 0.0162  memory: 45143  top1_acc: 0.5000  top5_acc: 0.8750  loss_cls: 1.6454  loss: 1.6454
2022/08/02 02:00:32 - mmengine - INFO - Epoch(train) [9][2800/3757]  lr: 8.3461e-05  eta: 15:33:26  time: 0.7315  data_time: 0.0162  memory: 45143  top1_acc: 0.7500  top5_acc: 0.7500  loss_cls: 1.7543  loss: 1.7543
2022/08/02 02:01:42 - mmengine - INFO - Epoch(train) [9][2900/3757]  lr: 8.3461e-05  eta: 15:32:15  time: 0.6899  data_time: 0.0146  memory: 45143  top1_acc: 0.3750  top5_acc: 0.3750  loss_cls: 1.7221  loss: 1.7221
2022/08/02 02:02:13 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 02:02:52 - mmengine - INFO - Epoch(train) [9][3000/3757]  lr: 8.3461e-05  eta: 15:31:05  time: 0.7045  data_time: 0.0145  memory: 45143  top1_acc: 0.5000  top5_acc: 0.6250  loss_cls: 1.7141  loss: 1.7141
2022/08/02 02:04:02 - mmengine - INFO - Epoch(train) [9][3100/3757]  lr: 8.3461e-05  eta: 15:29:54  time: 0.6945  data_time: 0.0143  memory: 45143  top1_acc: 0.5000  top5_acc: 0.8750  loss_cls: 1.4522  loss: 1.4522
2022/08/02 02:05:12 - mmengine - INFO - Epoch(train) [9][3200/3757]  lr: 8.3461e-05  eta: 15:28:44  time: 0.7014  data_time: 0.0167  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.9717  loss: 1.9717
2022/08/02 02:06:22 - mmengine - INFO - Epoch(train) [9][3300/3757]  lr: 8.3461e-05  eta: 15:27:32  time: 0.6924  data_time: 0.0147  memory: 45143  top1_acc: 0.6250  top5_acc: 0.6250  loss_cls: 1.3712  loss: 1.3712
2022/08/02 02:07:32 - mmengine - INFO - Epoch(train) [9][3400/3757]  lr: 8.3461e-05  eta: 15:26:21  time: 0.6980  data_time: 0.0159  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 1.6610  loss: 1.6610
2022/08/02 02:08:41 - mmengine - INFO - Epoch(train) [9][3500/3757]  lr: 8.3461e-05  eta: 15:25:10  time: 0.6906  data_time: 0.0144  memory: 45143  top1_acc: 0.2500  top5_acc: 0.7500  loss_cls: 1.6605  loss: 1.6605
2022/08/02 02:09:51 - mmengine - INFO - Epoch(train) [9][3600/3757]  lr: 8.3461e-05  eta: 15:23:59  time: 0.6967  data_time: 0.0166  memory: 45143  top1_acc: 0.5000  top5_acc: 0.8750  loss_cls: 1.3517  loss: 1.3517
2022/08/02 02:11:00 - mmengine - INFO - Epoch(train) [9][3700/3757]  lr: 8.3461e-05  eta: 15:22:47  time: 0.6904  data_time: 0.0148  memory: 45143  top1_acc: 0.6250  top5_acc: 1.0000  loss_cls: 1.6949  loss: 1.6949
2022/08/02 02:11:40 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 02:11:40 - mmengine - INFO - Epoch(train) [9][3757/3757]  lr: 8.3461e-05  eta: 15:22:19  time: 0.6815  data_time: 0.0152  memory: 45143  top1_acc: 0.5714  top5_acc: 0.7143  loss_cls: 1.4388  loss: 1.4388
2022/08/02 02:11:40 - mmengine - INFO - Saving checkpoint at 9 epochs
2022/08/02 02:12:12 - mmengine - INFO - Epoch(val) [9][100/310]    eta: 0:00:56  time: 0.2697  data_time: 0.0113  memory: 8742  
2022/08/02 02:12:40 - mmengine - INFO - Epoch(val) [9][200/310]    eta: 0:00:29  time: 0.2724  data_time: 0.0119  memory: 8742  
2022/08/02 02:13:07 - mmengine - INFO - Epoch(val) [9][300/310]    eta: 0:00:02  time: 0.2606  data_time: 0.0090  memory: 8742  
2022/08/02 02:13:10 - mmengine - INFO - Epoch(val) [9][310/310]  acc/top1: 0.6833  acc/top5: 0.8809  acc/mean1: 0.6831
2022/08/02 02:13:10 - mmengine - INFO - The previous best checkpoint /mnt/lustre/daiwenxun/X/mmaction2/work_dirs/swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb/best_acc/top1_epoch_7.pth is removed
2022/08/02 02:13:12 - mmengine - INFO - The best checkpoint with 0.6833 acc/top1 at 10 epoch is saved to best_acc/top1_epoch_10.pth.
2022/08/02 02:14:23 - mmengine - INFO - Epoch(train) [10][100/3757]  lr: 7.9393e-05  eta: 15:20:30  time: 0.6929  data_time: 0.0155  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.5661  loss: 1.5661
2022/08/02 02:15:23 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 02:15:32 - mmengine - INFO - Epoch(train) [10][200/3757]  lr: 7.9393e-05  eta: 15:19:19  time: 0.6927  data_time: 0.0156  memory: 45143  top1_acc: 0.5000  top5_acc: 0.6250  loss_cls: 1.8651  loss: 1.8651
2022/08/02 02:16:42 - mmengine - INFO - Epoch(train) [10][300/3757]  lr: 7.9393e-05  eta: 15:18:09  time: 0.6943  data_time: 0.0151  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.5194  loss: 1.5194
2022/08/02 02:17:52 - mmengine - INFO - Epoch(train) [10][400/3757]  lr: 7.9393e-05  eta: 15:16:58  time: 0.6951  data_time: 0.0158  memory: 45143  top1_acc: 0.5000  top5_acc: 0.8750  loss_cls: 1.5046  loss: 1.5046
2022/08/02 02:19:01 - mmengine - INFO - Epoch(train) [10][500/3757]  lr: 7.9393e-05  eta: 15:15:46  time: 0.6915  data_time: 0.0162  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 1.6817  loss: 1.6817
2022/08/02 02:20:11 - mmengine - INFO - Epoch(train) [10][600/3757]  lr: 7.9393e-05  eta: 15:14:34  time: 0.6909  data_time: 0.0159  memory: 45143  top1_acc: 0.1250  top5_acc: 0.6250  loss_cls: 1.5172  loss: 1.5172
2022/08/02 02:21:20 - mmengine - INFO - Epoch(train) [10][700/3757]  lr: 7.9393e-05  eta: 15:13:23  time: 0.6901  data_time: 0.0159  memory: 45143  top1_acc: 0.5000  top5_acc: 0.6250  loss_cls: 1.8037  loss: 1.8037
2022/08/02 02:22:30 - mmengine - INFO - Epoch(train) [10][800/3757]  lr: 7.9393e-05  eta: 15:12:11  time: 0.6896  data_time: 0.0150  memory: 45143  top1_acc: 0.7500  top5_acc: 0.7500  loss_cls: 1.5580  loss: 1.5580
2022/08/02 02:23:39 - mmengine - INFO - Epoch(train) [10][900/3757]  lr: 7.9393e-05  eta: 15:11:00  time: 0.6908  data_time: 0.0144  memory: 45143  top1_acc: 0.5000  top5_acc: 0.8750  loss_cls: 1.6113  loss: 1.6113
2022/08/02 02:24:49 - mmengine - INFO - Epoch(train) [10][1000/3757]  lr: 7.9393e-05  eta: 15:09:49  time: 0.6989  data_time: 0.0166  memory: 45143  top1_acc: 0.5000  top5_acc: 0.8750  loss_cls: 1.8711  loss: 1.8711
2022/08/02 02:25:59 - mmengine - INFO - Epoch(train) [10][1100/3757]  lr: 7.9393e-05  eta: 15:08:38  time: 0.6953  data_time: 0.0168  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 1.6525  loss: 1.6525
2022/08/02 02:26:59 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 02:27:08 - mmengine - INFO - Epoch(train) [10][1200/3757]  lr: 7.9393e-05  eta: 15:07:26  time: 0.6925  data_time: 0.0172  memory: 45143  top1_acc: 0.5000  top5_acc: 0.8750  loss_cls: 1.6154  loss: 1.6154
2022/08/02 02:28:18 - mmengine - INFO - Epoch(train) [10][1300/3757]  lr: 7.9393e-05  eta: 15:06:16  time: 0.7018  data_time: 0.0165  memory: 45143  top1_acc: 0.5000  top5_acc: 0.8750  loss_cls: 1.6349  loss: 1.6349
2022/08/02 02:29:28 - mmengine - INFO - Epoch(train) [10][1400/3757]  lr: 7.9393e-05  eta: 15:05:05  time: 0.6945  data_time: 0.0166  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 1.4016  loss: 1.4016
2022/08/02 02:30:37 - mmengine - INFO - Epoch(train) [10][1500/3757]  lr: 7.9393e-05  eta: 15:03:54  time: 0.6926  data_time: 0.0165  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 1.3789  loss: 1.3789
2022/08/02 02:31:47 - mmengine - INFO - Epoch(train) [10][1600/3757]  lr: 7.9393e-05  eta: 15:02:43  time: 0.6946  data_time: 0.0160  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.6787  loss: 1.6787
2022/08/02 02:32:57 - mmengine - INFO - Epoch(train) [10][1700/3757]  lr: 7.9393e-05  eta: 15:01:32  time: 0.6915  data_time: 0.0169  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 1.7122  loss: 1.7122
2022/08/02 02:34:06 - mmengine - INFO - Epoch(train) [10][1800/3757]  lr: 7.9393e-05  eta: 15:00:21  time: 0.6940  data_time: 0.0168  memory: 45143  top1_acc: 0.6250  top5_acc: 0.6250  loss_cls: 1.2394  loss: 1.2394
2022/08/02 02:35:16 - mmengine - INFO - Epoch(train) [10][1900/3757]  lr: 7.9393e-05  eta: 14:59:10  time: 0.6960  data_time: 0.0161  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.2892  loss: 1.2892
2022/08/02 02:36:26 - mmengine - INFO - Epoch(train) [10][2000/3757]  lr: 7.9393e-05  eta: 14:57:59  time: 0.6972  data_time: 0.0151  memory: 45143  top1_acc: 0.6250  top5_acc: 1.0000  loss_cls: 1.5315  loss: 1.5315
2022/08/02 02:37:35 - mmengine - INFO - Epoch(train) [10][2100/3757]  lr: 7.9393e-05  eta: 14:56:48  time: 0.6916  data_time: 0.0157  memory: 45143  top1_acc: 0.2500  top5_acc: 0.7500  loss_cls: 1.7649  loss: 1.7649
2022/08/02 02:38:36 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 02:38:45 - mmengine - INFO - Epoch(train) [10][2200/3757]  lr: 7.9393e-05  eta: 14:55:37  time: 0.6908  data_time: 0.0147  memory: 45143  top1_acc: 0.3750  top5_acc: 0.8750  loss_cls: 1.5217  loss: 1.5217
2022/08/02 02:39:55 - mmengine - INFO - Epoch(train) [10][2300/3757]  lr: 7.9393e-05  eta: 14:54:28  time: 0.6982  data_time: 0.0153  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 1.5978  loss: 1.5978
2022/08/02 02:41:05 - mmengine - INFO - Epoch(train) [10][2400/3757]  lr: 7.9393e-05  eta: 14:53:17  time: 0.6911  data_time: 0.0156  memory: 45143  top1_acc: 0.3750  top5_acc: 0.6250  loss_cls: 1.6592  loss: 1.6592
2022/08/02 02:42:15 - mmengine - INFO - Epoch(train) [10][2500/3757]  lr: 7.9393e-05  eta: 14:52:06  time: 0.6929  data_time: 0.0157  memory: 45143  top1_acc: 0.6250  top5_acc: 1.0000  loss_cls: 1.7257  loss: 1.7257
2022/08/02 02:43:24 - mmengine - INFO - Epoch(train) [10][2600/3757]  lr: 7.9393e-05  eta: 14:50:54  time: 0.6911  data_time: 0.0157  memory: 45143  top1_acc: 0.7500  top5_acc: 0.7500  loss_cls: 1.4699  loss: 1.4699
2022/08/02 02:44:34 - mmengine - INFO - Epoch(train) [10][2700/3757]  lr: 7.9393e-05  eta: 14:49:44  time: 0.7033  data_time: 0.0156  memory: 45143  top1_acc: 0.6250  top5_acc: 1.0000  loss_cls: 1.7217  loss: 1.7217
2022/08/02 02:45:44 - mmengine - INFO - Epoch(train) [10][2800/3757]  lr: 7.9393e-05  eta: 14:48:35  time: 0.6898  data_time: 0.0149  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 1.4591  loss: 1.4591
2022/08/02 02:46:54 - mmengine - INFO - Epoch(train) [10][2900/3757]  lr: 7.9393e-05  eta: 14:47:24  time: 0.6901  data_time: 0.0157  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.6120  loss: 1.6120
2022/08/02 02:48:03 - mmengine - INFO - Epoch(train) [10][3000/3757]  lr: 7.9393e-05  eta: 14:46:12  time: 0.6884  data_time: 0.0147  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.3279  loss: 1.3279
2022/08/02 02:49:13 - mmengine - INFO - Epoch(train) [10][3100/3757]  lr: 7.9393e-05  eta: 14:45:01  time: 0.6972  data_time: 0.0153  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 1.8527  loss: 1.8527
2022/08/02 02:50:13 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 02:50:22 - mmengine - INFO - Epoch(train) [10][3200/3757]  lr: 7.9393e-05  eta: 14:43:50  time: 0.6945  data_time: 0.0152  memory: 45143  top1_acc: 0.3750  top5_acc: 0.6250  loss_cls: 1.7610  loss: 1.7610
2022/08/02 02:51:32 - mmengine - INFO - Epoch(train) [10][3300/3757]  lr: 7.9393e-05  eta: 14:42:39  time: 0.6927  data_time: 0.0164  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.4242  loss: 1.4242
2022/08/02 02:52:42 - mmengine - INFO - Epoch(train) [10][3400/3757]  lr: 7.9393e-05  eta: 14:41:30  time: 0.6902  data_time: 0.0148  memory: 45143  top1_acc: 0.6250  top5_acc: 0.6250  loss_cls: 1.9822  loss: 1.9822
2022/08/02 02:53:53 - mmengine - INFO - Epoch(train) [10][3500/3757]  lr: 7.9393e-05  eta: 14:40:20  time: 0.6940  data_time: 0.0155  memory: 45143  top1_acc: 0.5000  top5_acc: 0.8750  loss_cls: 1.7062  loss: 1.7062
2022/08/02 02:55:02 - mmengine - INFO - Epoch(train) [10][3600/3757]  lr: 7.9393e-05  eta: 14:39:09  time: 0.6901  data_time: 0.0146  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 1.7046  loss: 1.7046
2022/08/02 02:56:12 - mmengine - INFO - Epoch(train) [10][3700/3757]  lr: 7.9393e-05  eta: 14:37:58  time: 0.6910  data_time: 0.0167  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.8161  loss: 1.8161
2022/08/02 02:56:52 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 02:56:52 - mmengine - INFO - Epoch(train) [10][3757/3757]  lr: 7.9393e-05  eta: 14:37:29  time: 0.6952  data_time: 0.0165  memory: 45143  top1_acc: 0.5714  top5_acc: 1.0000  loss_cls: 1.5698  loss: 1.5698
2022/08/02 02:58:03 - mmengine - INFO - Epoch(train) [11][100/3757]  lr: 7.5004e-05  eta: 14:35:47  time: 0.6904  data_time: 0.0145  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 1.4531  loss: 1.4531
2022/08/02 02:59:13 - mmengine - INFO - Epoch(train) [11][200/3757]  lr: 7.5004e-05  eta: 14:34:36  time: 0.6941  data_time: 0.0157  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.3725  loss: 1.3725
2022/08/02 03:00:23 - mmengine - INFO - Epoch(train) [11][300/3757]  lr: 7.5004e-05  eta: 14:33:25  time: 0.6908  data_time: 0.0139  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 1.6687  loss: 1.6687
2022/08/02 03:01:33 - mmengine - INFO - Epoch(train) [11][400/3757]  lr: 7.5004e-05  eta: 14:32:15  time: 0.7011  data_time: 0.0159  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.4929  loss: 1.4929
2022/08/02 03:01:53 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 03:02:42 - mmengine - INFO - Epoch(train) [11][500/3757]  lr: 7.5004e-05  eta: 14:31:04  time: 0.7024  data_time: 0.0157  memory: 45143  top1_acc: 0.5000  top5_acc: 0.8750  loss_cls: 1.5649  loss: 1.5649
2022/08/02 03:03:52 - mmengine - INFO - Epoch(train) [11][600/3757]  lr: 7.5004e-05  eta: 14:29:54  time: 0.6970  data_time: 0.0166  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 1.5389  loss: 1.5389
2022/08/02 03:05:02 - mmengine - INFO - Epoch(train) [11][700/3757]  lr: 7.5004e-05  eta: 14:28:43  time: 0.6966  data_time: 0.0166  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.5986  loss: 1.5986
2022/08/02 03:06:12 - mmengine - INFO - Epoch(train) [11][800/3757]  lr: 7.5004e-05  eta: 14:27:33  time: 0.6951  data_time: 0.0160  memory: 45143  top1_acc: 0.2500  top5_acc: 0.7500  loss_cls: 1.6507  loss: 1.6507
2022/08/02 03:07:21 - mmengine - INFO - Epoch(train) [11][900/3757]  lr: 7.5004e-05  eta: 14:26:22  time: 0.6998  data_time: 0.0164  memory: 45143  top1_acc: 0.3750  top5_acc: 0.7500  loss_cls: 1.6199  loss: 1.6199
2022/08/02 03:08:31 - mmengine - INFO - Epoch(train) [11][1000/3757]  lr: 7.5004e-05  eta: 14:25:11  time: 0.6966  data_time: 0.0155  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.4227  loss: 1.4227
2022/08/02 03:09:41 - mmengine - INFO - Epoch(train) [11][1100/3757]  lr: 7.5004e-05  eta: 14:24:01  time: 0.6998  data_time: 0.0159  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.7749  loss: 1.7749
2022/08/02 03:10:50 - mmengine - INFO - Epoch(train) [11][1200/3757]  lr: 7.5004e-05  eta: 14:22:50  time: 0.6941  data_time: 0.0165  memory: 45143  top1_acc: 0.6250  top5_acc: 1.0000  loss_cls: 1.6161  loss: 1.6161
2022/08/02 03:12:00 - mmengine - INFO - Epoch(train) [11][1300/3757]  lr: 7.5004e-05  eta: 14:21:39  time: 0.6908  data_time: 0.0167  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.7166  loss: 1.7166
2022/08/02 03:13:09 - mmengine - INFO - Epoch(train) [11][1400/3757]  lr: 7.5004e-05  eta: 14:20:28  time: 0.6905  data_time: 0.0156  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.6535  loss: 1.6535
2022/08/02 03:13:30 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 03:14:19 - mmengine - INFO - Epoch(train) [11][1500/3757]  lr: 7.5004e-05  eta: 14:19:17  time: 0.7011  data_time: 0.0162  memory: 45143  top1_acc: 0.3750  top5_acc: 0.7500  loss_cls: 1.3305  loss: 1.3305
2022/08/02 03:15:28 - mmengine - INFO - Epoch(train) [11][1600/3757]  lr: 7.5004e-05  eta: 14:18:06  time: 0.6934  data_time: 0.0146  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 1.4141  loss: 1.4141
2022/08/02 03:16:38 - mmengine - INFO - Epoch(train) [11][1700/3757]  lr: 7.5004e-05  eta: 14:16:56  time: 0.6920  data_time: 0.0158  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.5088  loss: 1.5088
2022/08/02 03:17:48 - mmengine - INFO - Epoch(train) [11][1800/3757]  lr: 7.5004e-05  eta: 14:15:46  time: 0.6909  data_time: 0.0145  memory: 45143  top1_acc: 0.5000  top5_acc: 0.8750  loss_cls: 1.5096  loss: 1.5096
2022/08/02 03:18:58 - mmengine - INFO - Epoch(train) [11][1900/3757]  lr: 7.5004e-05  eta: 14:14:36  time: 0.6922  data_time: 0.0164  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.3894  loss: 1.3894
2022/08/02 03:20:08 - mmengine - INFO - Epoch(train) [11][2000/3757]  lr: 7.5004e-05  eta: 14:13:25  time: 0.6971  data_time: 0.0169  memory: 45143  top1_acc: 0.7500  top5_acc: 0.7500  loss_cls: 1.4091  loss: 1.4091
2022/08/02 03:21:18 - mmengine - INFO - Epoch(train) [11][2100/3757]  lr: 7.5004e-05  eta: 14:12:15  time: 0.6910  data_time: 0.0157  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 1.3582  loss: 1.3582
2022/08/02 03:22:27 - mmengine - INFO - Epoch(train) [11][2200/3757]  lr: 7.5004e-05  eta: 14:11:03  time: 0.6906  data_time: 0.0152  memory: 45143  top1_acc: 0.3750  top5_acc: 0.6250  loss_cls: 1.9130  loss: 1.9130
2022/08/02 03:23:37 - mmengine - INFO - Epoch(train) [11][2300/3757]  lr: 7.5004e-05  eta: 14:09:52  time: 0.6926  data_time: 0.0168  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.3855  loss: 1.3855
2022/08/02 03:24:47 - mmengine - INFO - Epoch(train) [11][2400/3757]  lr: 7.5004e-05  eta: 14:08:43  time: 0.7093  data_time: 0.0149  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.5678  loss: 1.5678
2022/08/02 03:25:08 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 03:25:57 - mmengine - INFO - Epoch(train) [11][2500/3757]  lr: 7.5004e-05  eta: 14:07:33  time: 0.6909  data_time: 0.0159  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.3189  loss: 1.3189
2022/08/02 03:27:07 - mmengine - INFO - Epoch(train) [11][2600/3757]  lr: 7.5004e-05  eta: 14:06:22  time: 0.6965  data_time: 0.0156  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.7391  loss: 1.7391
2022/08/02 03:28:16 - mmengine - INFO - Epoch(train) [11][2700/3757]  lr: 7.5004e-05  eta: 14:05:12  time: 0.6957  data_time: 0.0155  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 1.7029  loss: 1.7029
2022/08/02 03:29:26 - mmengine - INFO - Epoch(train) [11][2800/3757]  lr: 7.5004e-05  eta: 14:04:02  time: 0.7013  data_time: 0.0158  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.4171  loss: 1.4171
2022/08/02 03:30:36 - mmengine - INFO - Epoch(train) [11][2900/3757]  lr: 7.5004e-05  eta: 14:02:51  time: 0.6914  data_time: 0.0150  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.6102  loss: 1.6102
2022/08/02 03:31:45 - mmengine - INFO - Epoch(train) [11][3000/3757]  lr: 7.5004e-05  eta: 14:01:40  time: 0.6960  data_time: 0.0158  memory: 45143  top1_acc: 0.2500  top5_acc: 0.6250  loss_cls: 1.6550  loss: 1.6550
2022/08/02 03:32:55 - mmengine - INFO - Epoch(train) [11][3100/3757]  lr: 7.5004e-05  eta: 14:00:29  time: 0.6997  data_time: 0.0170  memory: 45143  top1_acc: 0.3750  top5_acc: 0.7500  loss_cls: 1.3936  loss: 1.3936
2022/08/02 03:34:05 - mmengine - INFO - Epoch(train) [11][3200/3757]  lr: 7.5004e-05  eta: 13:59:19  time: 0.6980  data_time: 0.0162  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.7134  loss: 1.7134
2022/08/02 03:35:15 - mmengine - INFO - Epoch(train) [11][3300/3757]  lr: 7.5004e-05  eta: 13:58:08  time: 0.6936  data_time: 0.0157  memory: 45143  top1_acc: 0.5000  top5_acc: 0.8750  loss_cls: 1.4403  loss: 1.4403
2022/08/02 03:36:24 - mmengine - INFO - Epoch(train) [11][3400/3757]  lr: 7.5004e-05  eta: 13:56:58  time: 0.6976  data_time: 0.0155  memory: 45143  top1_acc: 0.5000  top5_acc: 0.8750  loss_cls: 1.5886  loss: 1.5886
2022/08/02 03:36:45 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 03:37:34 - mmengine - INFO - Epoch(train) [11][3500/3757]  lr: 7.5004e-05  eta: 13:55:48  time: 0.7040  data_time: 0.0175  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.8543  loss: 1.8543
2022/08/02 03:38:44 - mmengine - INFO - Epoch(train) [11][3600/3757]  lr: 7.5004e-05  eta: 13:54:37  time: 0.6993  data_time: 0.0164  memory: 45143  top1_acc: 0.5000  top5_acc: 0.8750  loss_cls: 1.3131  loss: 1.3131
2022/08/02 03:39:53 - mmengine - INFO - Epoch(train) [11][3700/3757]  lr: 7.5004e-05  eta: 13:53:26  time: 0.6938  data_time: 0.0160  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.5775  loss: 1.5775
2022/08/02 03:40:33 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 03:40:33 - mmengine - INFO - Epoch(train) [11][3757/3757]  lr: 7.5004e-05  eta: 13:52:58  time: 0.7034  data_time: 0.0174  memory: 45143  top1_acc: 0.5714  top5_acc: 1.0000  loss_cls: 1.3339  loss: 1.3339
2022/08/02 03:41:46 - mmengine - INFO - Epoch(train) [12][100/3757]  lr: 7.0340e-05  eta: 13:51:20  time: 0.7006  data_time: 0.0167  memory: 45143  top1_acc: 1.0000  top5_acc: 1.0000  loss_cls: 1.1377  loss: 1.1377
2022/08/02 03:42:56 - mmengine - INFO - Epoch(train) [12][200/3757]  lr: 7.0340e-05  eta: 13:50:10  time: 0.6933  data_time: 0.0165  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 1.4319  loss: 1.4319
2022/08/02 03:44:05 - mmengine - INFO - Epoch(train) [12][300/3757]  lr: 7.0340e-05  eta: 13:48:59  time: 0.6952  data_time: 0.0159  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 1.3030  loss: 1.3030
2022/08/02 03:45:15 - mmengine - INFO - Epoch(train) [12][400/3757]  lr: 7.0340e-05  eta: 13:47:49  time: 0.7034  data_time: 0.0169  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.5725  loss: 1.5725
2022/08/02 03:46:25 - mmengine - INFO - Epoch(train) [12][500/3757]  lr: 7.0340e-05  eta: 13:46:38  time: 0.7006  data_time: 0.0176  memory: 45143  top1_acc: 0.5000  top5_acc: 0.8750  loss_cls: 1.3386  loss: 1.3386
2022/08/02 03:47:35 - mmengine - INFO - Epoch(train) [12][600/3757]  lr: 7.0340e-05  eta: 13:45:28  time: 0.7024  data_time: 0.0166  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 1.3073  loss: 1.3073
2022/08/02 03:48:25 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 03:48:44 - mmengine - INFO - Epoch(train) [12][700/3757]  lr: 7.0340e-05  eta: 13:44:17  time: 0.6920  data_time: 0.0163  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.5755  loss: 1.5755
2022/08/02 03:49:54 - mmengine - INFO - Epoch(train) [12][800/3757]  lr: 7.0340e-05  eta: 13:43:06  time: 0.6928  data_time: 0.0157  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.4825  loss: 1.4825
2022/08/02 03:51:04 - mmengine - INFO - Epoch(train) [12][900/3757]  lr: 7.0340e-05  eta: 13:41:56  time: 0.7146  data_time: 0.0172  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 1.5825  loss: 1.5825
2022/08/02 03:52:13 - mmengine - INFO - Epoch(train) [12][1000/3757]  lr: 7.0340e-05  eta: 13:40:45  time: 0.6907  data_time: 0.0153  memory: 45143  top1_acc: 0.3750  top5_acc: 0.6250  loss_cls: 1.4034  loss: 1.4034
2022/08/02 03:53:23 - mmengine - INFO - Epoch(train) [12][1100/3757]  lr: 7.0340e-05  eta: 13:39:35  time: 0.6969  data_time: 0.0156  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 1.3708  loss: 1.3708
2022/08/02 03:54:32 - mmengine - INFO - Epoch(train) [12][1200/3757]  lr: 7.0340e-05  eta: 13:38:24  time: 0.6907  data_time: 0.0149  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.8094  loss: 1.8094
2022/08/02 03:55:42 - mmengine - INFO - Epoch(train) [12][1300/3757]  lr: 7.0340e-05  eta: 13:37:14  time: 0.6932  data_time: 0.0156  memory: 45143  top1_acc: 0.6250  top5_acc: 1.0000  loss_cls: 1.4562  loss: 1.4562
2022/08/02 03:56:52 - mmengine - INFO - Epoch(train) [12][1400/3757]  lr: 7.0340e-05  eta: 13:36:03  time: 0.6923  data_time: 0.0148  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.5370  loss: 1.5370
2022/08/02 03:58:02 - mmengine - INFO - Epoch(train) [12][1500/3757]  lr: 7.0340e-05  eta: 13:34:54  time: 0.7126  data_time: 0.0165  memory: 45143  top1_acc: 0.5000  top5_acc: 0.8750  loss_cls: 1.2261  loss: 1.2261
2022/08/02 03:59:11 - mmengine - INFO - Epoch(train) [12][1600/3757]  lr: 7.0340e-05  eta: 13:33:43  time: 0.6901  data_time: 0.0153  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.6842  loss: 1.6842
2022/08/02 04:00:02 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 04:00:21 - mmengine - INFO - Epoch(train) [12][1700/3757]  lr: 7.0340e-05  eta: 13:32:33  time: 0.7018  data_time: 0.0165  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.4204  loss: 1.4204
2022/08/02 04:01:31 - mmengine - INFO - Epoch(train) [12][1800/3757]  lr: 7.0340e-05  eta: 13:31:23  time: 0.6892  data_time: 0.0152  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 1.4103  loss: 1.4103
2022/08/02 04:02:41 - mmengine - INFO - Epoch(train) [12][1900/3757]  lr: 7.0340e-05  eta: 13:30:12  time: 0.6983  data_time: 0.0157  memory: 45143  top1_acc: 0.6250  top5_acc: 1.0000  loss_cls: 1.3105  loss: 1.3105
2022/08/02 04:03:50 - mmengine - INFO - Epoch(train) [12][2000/3757]  lr: 7.0340e-05  eta: 13:29:01  time: 0.6902  data_time: 0.0154  memory: 45143  top1_acc: 0.3750  top5_acc: 0.6250  loss_cls: 1.5126  loss: 1.5126
2022/08/02 04:05:00 - mmengine - INFO - Epoch(train) [12][2100/3757]  lr: 7.0340e-05  eta: 13:27:51  time: 0.7007  data_time: 0.0162  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.2206  loss: 1.2206
2022/08/02 04:06:09 - mmengine - INFO - Epoch(train) [12][2200/3757]  lr: 7.0340e-05  eta: 13:26:40  time: 0.6906  data_time: 0.0149  memory: 45143  top1_acc: 0.5000  top5_acc: 1.0000  loss_cls: 1.6824  loss: 1.6824
2022/08/02 04:07:19 - mmengine - INFO - Epoch(train) [12][2300/3757]  lr: 7.0340e-05  eta: 13:25:30  time: 0.6935  data_time: 0.0169  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.3918  loss: 1.3918
2022/08/02 04:08:28 - mmengine - INFO - Epoch(train) [12][2400/3757]  lr: 7.0340e-05  eta: 13:24:19  time: 0.6960  data_time: 0.0166  memory: 45143  top1_acc: 0.2500  top5_acc: 0.3750  loss_cls: 1.5286  loss: 1.5286
2022/08/02 04:09:38 - mmengine - INFO - Epoch(train) [12][2500/3757]  lr: 7.0340e-05  eta: 13:23:09  time: 0.7027  data_time: 0.0157  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.5056  loss: 1.5056
2022/08/02 04:10:48 - mmengine - INFO - Epoch(train) [12][2600/3757]  lr: 7.0340e-05  eta: 13:21:58  time: 0.6996  data_time: 0.0167  memory: 45143  top1_acc: 0.5000  top5_acc: 1.0000  loss_cls: 1.6873  loss: 1.6873
2022/08/02 04:11:39 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 04:11:57 - mmengine - INFO - Epoch(train) [12][2700/3757]  lr: 7.0340e-05  eta: 13:20:48  time: 0.6949  data_time: 0.0161  memory: 45143  top1_acc: 0.3750  top5_acc: 1.0000  loss_cls: 1.5315  loss: 1.5315
2022/08/02 04:13:07 - mmengine - INFO - Epoch(train) [12][2800/3757]  lr: 7.0340e-05  eta: 13:19:37  time: 0.6933  data_time: 0.0162  memory: 45143  top1_acc: 0.3750  top5_acc: 0.7500  loss_cls: 1.5950  loss: 1.5950
2022/08/02 04:14:17 - mmengine - INFO - Epoch(train) [12][2900/3757]  lr: 7.0340e-05  eta: 13:18:28  time: 0.6974  data_time: 0.0163  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.2468  loss: 1.2468
2022/08/02 04:15:27 - mmengine - INFO - Epoch(train) [12][3000/3757]  lr: 7.0340e-05  eta: 13:17:17  time: 0.6929  data_time: 0.0158  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 1.5937  loss: 1.5937
2022/08/02 04:16:37 - mmengine - INFO - Epoch(train) [12][3100/3757]  lr: 7.0340e-05  eta: 13:16:07  time: 0.6930  data_time: 0.0166  memory: 45143  top1_acc: 0.5000  top5_acc: 0.8750  loss_cls: 1.4043  loss: 1.4043
2022/08/02 04:17:46 - mmengine - INFO - Epoch(train) [12][3200/3757]  lr: 7.0340e-05  eta: 13:14:56  time: 0.6951  data_time: 0.0157  memory: 45143  top1_acc: 0.5000  top5_acc: 0.8750  loss_cls: 1.7974  loss: 1.7974
2022/08/02 04:18:56 - mmengine - INFO - Epoch(train) [12][3300/3757]  lr: 7.0340e-05  eta: 13:13:46  time: 0.6977  data_time: 0.0150  memory: 45143  top1_acc: 0.6250  top5_acc: 1.0000  loss_cls: 1.5220  loss: 1.5220
2022/08/02 04:20:06 - mmengine - INFO - Epoch(train) [12][3400/3757]  lr: 7.0340e-05  eta: 13:12:35  time: 0.6921  data_time: 0.0154  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.3449  loss: 1.3449
2022/08/02 04:21:16 - mmengine - INFO - Epoch(train) [12][3500/3757]  lr: 7.0340e-05  eta: 13:11:26  time: 0.6901  data_time: 0.0156  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.5079  loss: 1.5079
2022/08/02 04:22:26 - mmengine - INFO - Epoch(train) [12][3600/3757]  lr: 7.0340e-05  eta: 13:10:16  time: 0.7024  data_time: 0.0158  memory: 45143  top1_acc: 0.6250  top5_acc: 0.6250  loss_cls: 1.5110  loss: 1.5110
2022/08/02 04:23:17 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 04:23:35 - mmengine - INFO - Epoch(train) [12][3700/3757]  lr: 7.0340e-05  eta: 13:09:05  time: 0.6907  data_time: 0.0156  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.8129  loss: 1.8129
2022/08/02 04:24:15 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 04:24:15 - mmengine - INFO - Epoch(train) [12][3757/3757]  lr: 7.0340e-05  eta: 13:08:37  time: 0.6884  data_time: 0.0155  memory: 45143  top1_acc: 0.5714  top5_acc: 0.8571  loss_cls: 1.6100  loss: 1.6100
2022/08/02 04:24:15 - mmengine - INFO - Saving checkpoint at 12 epochs
2022/08/02 04:24:52 - mmengine - INFO - Epoch(val) [12][100/310]    eta: 0:00:57  time: 0.2719  data_time: 0.0121  memory: 8742  
2022/08/02 04:25:19 - mmengine - INFO - Epoch(val) [12][200/310]    eta: 0:00:31  time: 0.2841  data_time: 0.0129  memory: 8742  
2022/08/02 04:25:46 - mmengine - INFO - Epoch(val) [12][300/310]    eta: 0:00:02  time: 0.2597  data_time: 0.0088  memory: 8742  
2022/08/02 04:25:50 - mmengine - INFO - Epoch(val) [12][310/310]  acc/top1: 0.6964  acc/top5: 0.8868  acc/mean1: 0.6962
2022/08/02 04:25:50 - mmengine - INFO - The previous best checkpoint /mnt/lustre/daiwenxun/X/mmaction2/work_dirs/swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb/best_acc/top1_epoch_10.pth is removed
2022/08/02 04:25:53 - mmengine - INFO - The best checkpoint with 0.6964 acc/top1 at 13 epoch is saved to best_acc/top1_epoch_13.pth.
2022/08/02 04:27:04 - mmengine - INFO - Epoch(train) [13][100/3757]  lr: 6.5454e-05  eta: 13:06:59  time: 0.6938  data_time: 0.0163  memory: 45143  top1_acc: 0.6250  top5_acc: 0.6250  loss_cls: 1.2535  loss: 1.2535
2022/08/02 04:28:14 - mmengine - INFO - Epoch(train) [13][200/3757]  lr: 6.5454e-05  eta: 13:05:48  time: 0.6949  data_time: 0.0156  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 1.4196  loss: 1.4196
2022/08/02 04:29:23 - mmengine - INFO - Epoch(train) [13][300/3757]  lr: 6.5454e-05  eta: 13:04:38  time: 0.6931  data_time: 0.0162  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.4532  loss: 1.4532
2022/08/02 04:30:33 - mmengine - INFO - Epoch(train) [13][400/3757]  lr: 6.5454e-05  eta: 13:03:29  time: 0.6932  data_time: 0.0158  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.4665  loss: 1.4665
2022/08/02 04:31:43 - mmengine - INFO - Epoch(train) [13][500/3757]  lr: 6.5454e-05  eta: 13:02:18  time: 0.6922  data_time: 0.0152  memory: 45143  top1_acc: 0.7500  top5_acc: 0.7500  loss_cls: 1.2986  loss: 1.2986
2022/08/02 04:32:53 - mmengine - INFO - Epoch(train) [13][600/3757]  lr: 6.5454e-05  eta: 13:01:08  time: 0.7042  data_time: 0.0153  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.5358  loss: 1.5358
2022/08/02 04:34:03 - mmengine - INFO - Epoch(train) [13][700/3757]  lr: 6.5454e-05  eta: 12:59:59  time: 0.6961  data_time: 0.0155  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.3169  loss: 1.3169
2022/08/02 04:35:13 - mmengine - INFO - Epoch(train) [13][800/3757]  lr: 6.5454e-05  eta: 12:58:49  time: 0.6922  data_time: 0.0160  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.6523  loss: 1.6523
2022/08/02 04:36:23 - mmengine - INFO - Epoch(train) [13][900/3757]  lr: 6.5454e-05  eta: 12:57:39  time: 0.6957  data_time: 0.0151  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.5015  loss: 1.5015
2022/08/02 04:36:35 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 04:37:34 - mmengine - INFO - Epoch(train) [13][1000/3757]  lr: 6.5454e-05  eta: 12:56:30  time: 0.6948  data_time: 0.0159  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.4296  loss: 1.4296
2022/08/02 04:38:44 - mmengine - INFO - Epoch(train) [13][1100/3757]  lr: 6.5454e-05  eta: 12:55:20  time: 0.6919  data_time: 0.0154  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 1.4564  loss: 1.4564
2022/08/02 04:39:54 - mmengine - INFO - Epoch(train) [13][1200/3757]  lr: 6.5454e-05  eta: 12:54:11  time: 0.7116  data_time: 0.0156  memory: 45143  top1_acc: 0.3750  top5_acc: 0.5000  loss_cls: 1.5458  loss: 1.5458
2022/08/02 04:41:04 - mmengine - INFO - Epoch(train) [13][1300/3757]  lr: 6.5454e-05  eta: 12:53:01  time: 0.6962  data_time: 0.0162  memory: 45143  top1_acc: 0.3750  top5_acc: 0.6250  loss_cls: 1.6798  loss: 1.6798
2022/08/02 04:42:14 - mmengine - INFO - Epoch(train) [13][1400/3757]  lr: 6.5454e-05  eta: 12:51:51  time: 0.7015  data_time: 0.0153  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.4373  loss: 1.4373
2022/08/02 04:43:24 - mmengine - INFO - Epoch(train) [13][1500/3757]  lr: 6.5454e-05  eta: 12:50:41  time: 0.6948  data_time: 0.0153  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.4746  loss: 1.4746
2022/08/02 04:44:34 - mmengine - INFO - Epoch(train) [13][1600/3757]  lr: 6.5454e-05  eta: 12:49:31  time: 0.7013  data_time: 0.0165  memory: 45143  top1_acc: 0.6250  top5_acc: 1.0000  loss_cls: 1.3602  loss: 1.3602
2022/08/02 04:45:44 - mmengine - INFO - Epoch(train) [13][1700/3757]  lr: 6.5454e-05  eta: 12:48:21  time: 0.6904  data_time: 0.0161  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.6870  loss: 1.6870
2022/08/02 04:46:54 - mmengine - INFO - Epoch(train) [13][1800/3757]  lr: 6.5454e-05  eta: 12:47:11  time: 0.6930  data_time: 0.0166  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.4167  loss: 1.4167
2022/08/02 04:48:04 - mmengine - INFO - Epoch(train) [13][1900/3757]  lr: 6.5454e-05  eta: 12:46:01  time: 0.6900  data_time: 0.0155  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.5784  loss: 1.5784
2022/08/02 04:48:15 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 04:49:14 - mmengine - INFO - Epoch(train) [13][2000/3757]  lr: 6.5454e-05  eta: 12:44:52  time: 0.7027  data_time: 0.0170  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 1.3178  loss: 1.3178
2022/08/02 04:50:24 - mmengine - INFO - Epoch(train) [13][2100/3757]  lr: 6.5454e-05  eta: 12:43:42  time: 0.6896  data_time: 0.0145  memory: 45143  top1_acc: 0.5000  top5_acc: 0.6250  loss_cls: 1.4837  loss: 1.4837
2022/08/02 04:51:34 - mmengine - INFO - Epoch(train) [13][2200/3757]  lr: 6.5454e-05  eta: 12:42:32  time: 0.6916  data_time: 0.0165  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.5185  loss: 1.5185
2022/08/02 04:52:44 - mmengine - INFO - Epoch(train) [13][2300/3757]  lr: 6.5454e-05  eta: 12:41:22  time: 0.6916  data_time: 0.0147  memory: 45143  top1_acc: 0.1250  top5_acc: 0.8750  loss_cls: 1.3535  loss: 1.3535
2022/08/02 04:53:54 - mmengine - INFO - Epoch(train) [13][2400/3757]  lr: 6.5454e-05  eta: 12:40:13  time: 0.7043  data_time: 0.0163  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.2178  loss: 1.2178
2022/08/02 04:55:04 - mmengine - INFO - Epoch(train) [13][2500/3757]  lr: 6.5454e-05  eta: 12:39:03  time: 0.6947  data_time: 0.0161  memory: 45143  top1_acc: 0.5000  top5_acc: 0.8750  loss_cls: 1.5371  loss: 1.5371
2022/08/02 04:56:14 - mmengine - INFO - Epoch(train) [13][2600/3757]  lr: 6.5454e-05  eta: 12:37:52  time: 0.6969  data_time: 0.0149  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.2393  loss: 1.2393
2022/08/02 04:57:23 - mmengine - INFO - Epoch(train) [13][2700/3757]  lr: 6.5454e-05  eta: 12:36:41  time: 0.6985  data_time: 0.0172  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.4175  loss: 1.4175
2022/08/02 04:58:33 - mmengine - INFO - Epoch(train) [13][2800/3757]  lr: 6.5454e-05  eta: 12:35:32  time: 0.7199  data_time: 0.0174  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.9072  loss: 1.9072
2022/08/02 04:59:43 - mmengine - INFO - Epoch(train) [13][2900/3757]  lr: 6.5454e-05  eta: 12:34:21  time: 0.7036  data_time: 0.0166  memory: 45143  top1_acc: 0.3750  top5_acc: 1.0000  loss_cls: 1.3244  loss: 1.3244
2022/08/02 04:59:54 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 05:00:53 - mmengine - INFO - Epoch(train) [13][3000/3757]  lr: 6.5454e-05  eta: 12:33:12  time: 0.7058  data_time: 0.0153  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.3182  loss: 1.3182
2022/08/02 05:02:03 - mmengine - INFO - Epoch(train) [13][3100/3757]  lr: 6.5454e-05  eta: 12:32:02  time: 0.7056  data_time: 0.0177  memory: 45143  top1_acc: 0.6250  top5_acc: 1.0000  loss_cls: 1.4644  loss: 1.4644
2022/08/02 05:03:13 - mmengine - INFO - Epoch(train) [13][3200/3757]  lr: 6.5454e-05  eta: 12:30:52  time: 0.7006  data_time: 0.0195  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.6136  loss: 1.6136
2022/08/02 05:04:22 - mmengine - INFO - Epoch(train) [13][3300/3757]  lr: 6.5454e-05  eta: 12:29:42  time: 0.6917  data_time: 0.0170  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 1.5954  loss: 1.5954
2022/08/02 05:05:32 - mmengine - INFO - Epoch(train) [13][3400/3757]  lr: 6.5454e-05  eta: 12:28:31  time: 0.6931  data_time: 0.0162  memory: 45143  top1_acc: 0.3750  top5_acc: 1.0000  loss_cls: 1.7142  loss: 1.7142
2022/08/02 05:06:41 - mmengine - INFO - Epoch(train) [13][3500/3757]  lr: 6.5454e-05  eta: 12:27:20  time: 0.6909  data_time: 0.0163  memory: 45143  top1_acc: 1.0000  top5_acc: 1.0000  loss_cls: 1.2092  loss: 1.2092
2022/08/02 05:07:51 - mmengine - INFO - Epoch(train) [13][3600/3757]  lr: 6.5454e-05  eta: 12:26:10  time: 0.6943  data_time: 0.0167  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.5910  loss: 1.5910
2022/08/02 05:09:00 - mmengine - INFO - Epoch(train) [13][3700/3757]  lr: 6.5454e-05  eta: 12:24:59  time: 0.6953  data_time: 0.0168  memory: 45143  top1_acc: 0.3750  top5_acc: 0.7500  loss_cls: 1.4706  loss: 1.4706
2022/08/02 05:09:40 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 05:09:40 - mmengine - INFO - Epoch(train) [13][3757/3757]  lr: 6.5454e-05  eta: 12:24:31  time: 0.6946  data_time: 0.0180  memory: 45143  top1_acc: 0.8571  top5_acc: 0.8571  loss_cls: 1.3296  loss: 1.3296
2022/08/02 05:10:51 - mmengine - INFO - Epoch(train) [14][100/3757]  lr: 6.0398e-05  eta: 12:22:56  time: 0.6909  data_time: 0.0147  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.4612  loss: 1.4612
2022/08/02 05:11:33 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 05:12:01 - mmengine - INFO - Epoch(train) [14][200/3757]  lr: 6.0398e-05  eta: 12:21:45  time: 0.6998  data_time: 0.0157  memory: 45143  top1_acc: 0.6250  top5_acc: 1.0000  loss_cls: 1.7456  loss: 1.7456
2022/08/02 05:13:11 - mmengine - INFO - Epoch(train) [14][300/3757]  lr: 6.0398e-05  eta: 12:20:35  time: 0.6981  data_time: 0.0160  memory: 45143  top1_acc: 0.1250  top5_acc: 0.8750  loss_cls: 1.4085  loss: 1.4085
2022/08/02 05:14:21 - mmengine - INFO - Epoch(train) [14][400/3757]  lr: 6.0398e-05  eta: 12:19:26  time: 0.6999  data_time: 0.0155  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.1404  loss: 1.1404
2022/08/02 05:15:31 - mmengine - INFO - Epoch(train) [14][500/3757]  lr: 6.0398e-05  eta: 12:18:16  time: 0.6931  data_time: 0.0144  memory: 45143  top1_acc: 0.3750  top5_acc: 0.7500  loss_cls: 1.4410  loss: 1.4410
2022/08/02 05:16:41 - mmengine - INFO - Epoch(train) [14][600/3757]  lr: 6.0398e-05  eta: 12:17:06  time: 0.6909  data_time: 0.0156  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 1.1720  loss: 1.1720
2022/08/02 05:17:50 - mmengine - INFO - Epoch(train) [14][700/3757]  lr: 6.0398e-05  eta: 12:15:56  time: 0.6969  data_time: 0.0154  memory: 45143  top1_acc: 0.6250  top5_acc: 1.0000  loss_cls: 1.0992  loss: 1.0992
2022/08/02 05:19:00 - mmengine - INFO - Epoch(train) [14][800/3757]  lr: 6.0398e-05  eta: 12:14:45  time: 0.6900  data_time: 0.0152  memory: 45143  top1_acc: 1.0000  top5_acc: 1.0000  loss_cls: 1.5945  loss: 1.5945
2022/08/02 05:20:09 - mmengine - INFO - Epoch(train) [14][900/3757]  lr: 6.0398e-05  eta: 12:13:35  time: 0.6924  data_time: 0.0158  memory: 45143  top1_acc: 0.5000  top5_acc: 0.8750  loss_cls: 1.2941  loss: 1.2941
2022/08/02 05:21:19 - mmengine - INFO - Epoch(train) [14][1000/3757]  lr: 6.0398e-05  eta: 12:12:25  time: 0.6909  data_time: 0.0149  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.4987  loss: 1.4987
2022/08/02 05:22:29 - mmengine - INFO - Epoch(train) [14][1100/3757]  lr: 6.0398e-05  eta: 12:11:15  time: 0.6987  data_time: 0.0161  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.3697  loss: 1.3697
2022/08/02 05:23:10 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 05:23:39 - mmengine - INFO - Epoch(train) [14][1200/3757]  lr: 6.0398e-05  eta: 12:10:04  time: 0.6934  data_time: 0.0147  memory: 45143  top1_acc: 0.5000  top5_acc: 0.8750  loss_cls: 1.4774  loss: 1.4774
2022/08/02 05:24:48 - mmengine - INFO - Epoch(train) [14][1300/3757]  lr: 6.0398e-05  eta: 12:08:54  time: 0.6922  data_time: 0.0150  memory: 45143  top1_acc: 0.5000  top5_acc: 0.6250  loss_cls: 1.4336  loss: 1.4336
2022/08/02 05:25:58 - mmengine - INFO - Epoch(train) [14][1400/3757]  lr: 6.0398e-05  eta: 12:07:43  time: 0.6905  data_time: 0.0155  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.1996  loss: 1.1996
2022/08/02 05:27:08 - mmengine - INFO - Epoch(train) [14][1500/3757]  lr: 6.0398e-05  eta: 12:06:34  time: 0.7096  data_time: 0.0174  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 1.6232  loss: 1.6232
2022/08/02 05:28:18 - mmengine - INFO - Epoch(train) [14][1600/3757]  lr: 6.0398e-05  eta: 12:05:24  time: 0.6937  data_time: 0.0151  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.5897  loss: 1.5897
2022/08/02 05:29:27 - mmengine - INFO - Epoch(train) [14][1700/3757]  lr: 6.0398e-05  eta: 12:04:14  time: 0.6906  data_time: 0.0152  memory: 45143  top1_acc: 0.3750  top5_acc: 0.6250  loss_cls: 1.5533  loss: 1.5533
2022/08/02 05:30:38 - mmengine - INFO - Epoch(train) [14][1800/3757]  lr: 6.0398e-05  eta: 12:03:04  time: 0.6940  data_time: 0.0156  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 1.3013  loss: 1.3013
2022/08/02 05:31:48 - mmengine - INFO - Epoch(train) [14][1900/3757]  lr: 6.0398e-05  eta: 12:01:55  time: 0.6916  data_time: 0.0157  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.3998  loss: 1.3998
2022/08/02 05:32:58 - mmengine - INFO - Epoch(train) [14][2000/3757]  lr: 6.0398e-05  eta: 12:00:45  time: 0.6992  data_time: 0.0160  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.8527  loss: 1.8527
2022/08/02 05:34:08 - mmengine - INFO - Epoch(train) [14][2100/3757]  lr: 6.0398e-05  eta: 11:59:36  time: 0.6934  data_time: 0.0158  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.3727  loss: 1.3727
2022/08/02 05:34:49 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 05:35:18 - mmengine - INFO - Epoch(train) [14][2200/3757]  lr: 6.0398e-05  eta: 11:58:26  time: 0.6982  data_time: 0.0158  memory: 45143  top1_acc: 0.7500  top5_acc: 0.7500  loss_cls: 1.4487  loss: 1.4487
2022/08/02 05:36:28 - mmengine - INFO - Epoch(train) [14][2300/3757]  lr: 6.0398e-05  eta: 11:57:15  time: 0.6953  data_time: 0.0170  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 1.2726  loss: 1.2726
2022/08/02 05:37:37 - mmengine - INFO - Epoch(train) [14][2400/3757]  lr: 6.0398e-05  eta: 11:56:05  time: 0.6948  data_time: 0.0162  memory: 45143  top1_acc: 0.6250  top5_acc: 1.0000  loss_cls: 1.5276  loss: 1.5276
2022/08/02 05:38:47 - mmengine - INFO - Epoch(train) [14][2500/3757]  lr: 6.0398e-05  eta: 11:54:55  time: 0.6941  data_time: 0.0158  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 1.6194  loss: 1.6194
2022/08/02 05:39:57 - mmengine - INFO - Epoch(train) [14][2600/3757]  lr: 6.0398e-05  eta: 11:53:45  time: 0.6974  data_time: 0.0160  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.3966  loss: 1.3966
2022/08/02 05:41:07 - mmengine - INFO - Epoch(train) [14][2700/3757]  lr: 6.0398e-05  eta: 11:52:35  time: 0.7073  data_time: 0.0175  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.6370  loss: 1.6370
2022/08/02 05:42:17 - mmengine - INFO - Epoch(train) [14][2800/3757]  lr: 6.0398e-05  eta: 11:51:25  time: 0.6953  data_time: 0.0154  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 1.3740  loss: 1.3740
2022/08/02 05:43:27 - mmengine - INFO - Epoch(train) [14][2900/3757]  lr: 6.0398e-05  eta: 11:50:16  time: 0.7139  data_time: 0.0167  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.5060  loss: 1.5060
2022/08/02 05:44:37 - mmengine - INFO - Epoch(train) [14][3000/3757]  lr: 6.0398e-05  eta: 11:49:06  time: 0.7045  data_time: 0.0168  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.5481  loss: 1.5481
2022/08/02 05:45:47 - mmengine - INFO - Epoch(train) [14][3100/3757]  lr: 6.0398e-05  eta: 11:47:56  time: 0.6962  data_time: 0.0154  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 1.7246  loss: 1.7246
2022/08/02 05:46:28 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 05:46:57 - mmengine - INFO - Epoch(train) [14][3200/3757]  lr: 6.0398e-05  eta: 11:46:46  time: 0.6927  data_time: 0.0172  memory: 45143  top1_acc: 0.5000  top5_acc: 0.8750  loss_cls: 1.0504  loss: 1.0504
2022/08/02 05:48:06 - mmengine - INFO - Epoch(train) [14][3300/3757]  lr: 6.0398e-05  eta: 11:45:36  time: 0.7051  data_time: 0.0159  memory: 45143  top1_acc: 0.6250  top5_acc: 1.0000  loss_cls: 1.2649  loss: 1.2649
2022/08/02 05:49:17 - mmengine - INFO - Epoch(train) [14][3400/3757]  lr: 6.0398e-05  eta: 11:44:26  time: 0.7065  data_time: 0.0200  memory: 45143  top1_acc: 0.5000  top5_acc: 0.8750  loss_cls: 1.4315  loss: 1.4315
2022/08/02 05:50:26 - mmengine - INFO - Epoch(train) [14][3500/3757]  lr: 6.0398e-05  eta: 11:43:16  time: 0.6951  data_time: 0.0165  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 1.5198  loss: 1.5198
2022/08/02 05:51:36 - mmengine - INFO - Epoch(train) [14][3600/3757]  lr: 6.0398e-05  eta: 11:42:06  time: 0.6951  data_time: 0.0159  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.4713  loss: 1.4713
2022/08/02 05:52:46 - mmengine - INFO - Epoch(train) [14][3700/3757]  lr: 6.0398e-05  eta: 11:40:56  time: 0.6925  data_time: 0.0164  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.1973  loss: 1.1973
2022/08/02 05:53:26 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 05:53:26 - mmengine - INFO - Epoch(train) [14][3757/3757]  lr: 6.0398e-05  eta: 11:40:28  time: 0.7075  data_time: 0.0183  memory: 45143  top1_acc: 0.4286  top5_acc: 0.7143  loss_cls: 1.2499  loss: 1.2499
2022/08/02 05:54:38 - mmengine - INFO - Epoch(train) [15][100/3757]  lr: 5.5229e-05  eta: 11:38:55  time: 0.6962  data_time: 0.0162  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 1.3095  loss: 1.3095
2022/08/02 05:55:47 - mmengine - INFO - Epoch(train) [15][200/3757]  lr: 5.5229e-05  eta: 11:37:45  time: 0.6935  data_time: 0.0162  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.1719  loss: 1.1719
2022/08/02 05:56:57 - mmengine - INFO - Epoch(train) [15][300/3757]  lr: 5.5229e-05  eta: 11:36:35  time: 0.6977  data_time: 0.0170  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 1.2666  loss: 1.2666
2022/08/02 05:58:07 - mmengine - INFO - Epoch(train) [15][400/3757]  lr: 5.5229e-05  eta: 11:35:25  time: 0.7116  data_time: 0.0171  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.4444  loss: 1.4444
2022/08/02 05:58:09 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 05:59:17 - mmengine - INFO - Epoch(train) [15][500/3757]  lr: 5.5229e-05  eta: 11:34:15  time: 0.7159  data_time: 0.0176  memory: 45143  top1_acc: 1.0000  top5_acc: 1.0000  loss_cls: 1.4723  loss: 1.4723
2022/08/02 06:00:28 - mmengine - INFO - Epoch(train) [15][600/3757]  lr: 5.5229e-05  eta: 11:33:07  time: 0.7037  data_time: 0.0160  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 1.0122  loss: 1.0122
2022/08/02 06:01:38 - mmengine - INFO - Epoch(train) [15][700/3757]  lr: 5.5229e-05  eta: 11:31:56  time: 0.6949  data_time: 0.0169  memory: 45143  top1_acc: 0.5000  top5_acc: 0.6250  loss_cls: 1.3777  loss: 1.3777
2022/08/02 06:02:48 - mmengine - INFO - Epoch(train) [15][800/3757]  lr: 5.5229e-05  eta: 11:30:47  time: 0.7025  data_time: 0.0163  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.3951  loss: 1.3951
2022/08/02 06:03:57 - mmengine - INFO - Epoch(train) [15][900/3757]  lr: 5.5229e-05  eta: 11:29:36  time: 0.6922  data_time: 0.0158  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.5613  loss: 1.5613
2022/08/02 06:05:07 - mmengine - INFO - Epoch(train) [15][1000/3757]  lr: 5.5229e-05  eta: 11:28:26  time: 0.7028  data_time: 0.0166  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 1.5059  loss: 1.5059
2022/08/02 06:06:17 - mmengine - INFO - Epoch(train) [15][1100/3757]  lr: 5.5229e-05  eta: 11:27:16  time: 0.6961  data_time: 0.0155  memory: 45143  top1_acc: 0.6250  top5_acc: 1.0000  loss_cls: 1.3609  loss: 1.3609
2022/08/02 06:07:26 - mmengine - INFO - Epoch(train) [15][1200/3757]  lr: 5.5229e-05  eta: 11:26:05  time: 0.6905  data_time: 0.0161  memory: 45143  top1_acc: 1.0000  top5_acc: 1.0000  loss_cls: 1.3027  loss: 1.3027
2022/08/02 06:08:35 - mmengine - INFO - Epoch(train) [15][1300/3757]  lr: 5.5229e-05  eta: 11:24:55  time: 0.6954  data_time: 0.0161  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.1180  loss: 1.1180
2022/08/02 06:09:45 - mmengine - INFO - Epoch(train) [15][1400/3757]  lr: 5.5229e-05  eta: 11:23:45  time: 0.6922  data_time: 0.0169  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.3225  loss: 1.3225
2022/08/02 06:09:46 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 06:10:54 - mmengine - INFO - Epoch(train) [15][1500/3757]  lr: 5.5229e-05  eta: 11:22:34  time: 0.6925  data_time: 0.0145  memory: 45143  top1_acc: 0.6250  top5_acc: 0.6250  loss_cls: 1.3622  loss: 1.3622
2022/08/02 06:12:04 - mmengine - INFO - Epoch(train) [15][1600/3757]  lr: 5.5229e-05  eta: 11:21:24  time: 0.6929  data_time: 0.0160  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.4387  loss: 1.4387
2022/08/02 06:13:14 - mmengine - INFO - Epoch(train) [15][1700/3757]  lr: 5.5229e-05  eta: 11:20:14  time: 0.6922  data_time: 0.0153  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.0844  loss: 1.0844
2022/08/02 06:14:24 - mmengine - INFO - Epoch(train) [15][1800/3757]  lr: 5.5229e-05  eta: 11:19:04  time: 0.6936  data_time: 0.0160  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 1.5758  loss: 1.5758
2022/08/02 06:15:33 - mmengine - INFO - Epoch(train) [15][1900/3757]  lr: 5.5229e-05  eta: 11:17:54  time: 0.6909  data_time: 0.0151  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.3194  loss: 1.3194
2022/08/02 06:16:43 - mmengine - INFO - Epoch(train) [15][2000/3757]  lr: 5.5229e-05  eta: 11:16:44  time: 0.7036  data_time: 0.0160  memory: 45143  top1_acc: 0.5000  top5_acc: 0.6250  loss_cls: 1.5489  loss: 1.5489
2022/08/02 06:17:53 - mmengine - INFO - Epoch(train) [15][2100/3757]  lr: 5.5229e-05  eta: 11:15:34  time: 0.6931  data_time: 0.0154  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.2120  loss: 1.2120
2022/08/02 06:19:02 - mmengine - INFO - Epoch(train) [15][2200/3757]  lr: 5.5229e-05  eta: 11:14:24  time: 0.6905  data_time: 0.0159  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.4057  loss: 1.4057
2022/08/02 06:20:12 - mmengine - INFO - Epoch(train) [15][2300/3757]  lr: 5.5229e-05  eta: 11:13:13  time: 0.6919  data_time: 0.0161  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.5674  loss: 1.5674
2022/08/02 06:21:21 - mmengine - INFO - Epoch(train) [15][2400/3757]  lr: 5.5229e-05  eta: 11:12:03  time: 0.7011  data_time: 0.0160  memory: 45143  top1_acc: 0.5000  top5_acc: 0.8750  loss_cls: 1.5682  loss: 1.5682
2022/08/02 06:21:23 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 06:22:31 - mmengine - INFO - Epoch(train) [15][2500/3757]  lr: 5.5229e-05  eta: 11:10:54  time: 0.7041  data_time: 0.0165  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 1.6330  loss: 1.6330
2022/08/02 06:23:41 - mmengine - INFO - Epoch(train) [15][2600/3757]  lr: 5.5229e-05  eta: 11:09:44  time: 0.6984  data_time: 0.0168  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.6161  loss: 1.6161
2022/08/02 06:24:51 - mmengine - INFO - Epoch(train) [15][2700/3757]  lr: 5.5229e-05  eta: 11:08:34  time: 0.7059  data_time: 0.0166  memory: 45143  top1_acc: 0.5000  top5_acc: 0.8750  loss_cls: 1.2995  loss: 1.2995
2022/08/02 06:26:01 - mmengine - INFO - Epoch(train) [15][2800/3757]  lr: 5.5229e-05  eta: 11:07:24  time: 0.7079  data_time: 0.0167  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.1451  loss: 1.1451
2022/08/02 06:27:11 - mmengine - INFO - Epoch(train) [15][2900/3757]  lr: 5.5229e-05  eta: 11:06:14  time: 0.6983  data_time: 0.0166  memory: 45143  top1_acc: 1.0000  top5_acc: 1.0000  loss_cls: 1.1982  loss: 1.1982
2022/08/02 06:28:21 - mmengine - INFO - Epoch(train) [15][3000/3757]  lr: 5.5229e-05  eta: 11:05:04  time: 0.7035  data_time: 0.0154  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.3893  loss: 1.3893
2022/08/02 06:29:30 - mmengine - INFO - Epoch(train) [15][3100/3757]  lr: 5.5229e-05  eta: 11:03:54  time: 0.6926  data_time: 0.0171  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.3804  loss: 1.3804
2022/08/02 06:30:40 - mmengine - INFO - Epoch(train) [15][3200/3757]  lr: 5.5229e-05  eta: 11:02:44  time: 0.6979  data_time: 0.0161  memory: 45143  top1_acc: 0.2500  top5_acc: 0.8750  loss_cls: 1.2285  loss: 1.2285
2022/08/02 06:31:50 - mmengine - INFO - Epoch(train) [15][3300/3757]  lr: 5.5229e-05  eta: 11:01:34  time: 0.7121  data_time: 0.0175  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 1.5363  loss: 1.5363
2022/08/02 06:33:00 - mmengine - INFO - Epoch(train) [15][3400/3757]  lr: 5.5229e-05  eta: 11:00:24  time: 0.7088  data_time: 0.0162  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.2632  loss: 1.2632
2022/08/02 06:33:01 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 06:34:10 - mmengine - INFO - Epoch(train) [15][3500/3757]  lr: 5.5229e-05  eta: 10:59:15  time: 0.7173  data_time: 0.0186  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 0.9894  loss: 0.9894
2022/08/02 06:35:20 - mmengine - INFO - Epoch(train) [15][3600/3757]  lr: 5.5229e-05  eta: 10:58:05  time: 0.7070  data_time: 0.0169  memory: 45143  top1_acc: 0.5000  top5_acc: 0.8750  loss_cls: 1.3922  loss: 1.3922
2022/08/02 06:36:30 - mmengine - INFO - Epoch(train) [15][3700/3757]  lr: 5.5229e-05  eta: 10:56:55  time: 0.6958  data_time: 0.0161  memory: 45143  top1_acc: 0.6250  top5_acc: 1.0000  loss_cls: 1.1712  loss: 1.1712
2022/08/02 06:37:09 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 06:37:09 - mmengine - INFO - Epoch(train) [15][3757/3757]  lr: 5.5229e-05  eta: 10:56:27  time: 0.6979  data_time: 0.0151  memory: 45143  top1_acc: 0.8571  top5_acc: 1.0000  loss_cls: 1.1803  loss: 1.1803
2022/08/02 06:37:10 - mmengine - INFO - Saving checkpoint at 15 epochs
2022/08/02 06:37:47 - mmengine - INFO - Epoch(val) [15][100/310]    eta: 0:00:56  time: 0.2697  data_time: 0.0113  memory: 8742  
2022/08/02 06:38:14 - mmengine - INFO - Epoch(val) [15][200/310]    eta: 0:00:31  time: 0.2860  data_time: 0.0150  memory: 8742  
2022/08/02 06:38:42 - mmengine - INFO - Epoch(val) [15][300/310]    eta: 0:00:02  time: 0.2638  data_time: 0.0113  memory: 8742  
2022/08/02 06:38:45 - mmengine - INFO - Epoch(val) [15][310/310]  acc/top1: 0.7098  acc/top5: 0.8965  acc/mean1: 0.7096
2022/08/02 06:38:45 - mmengine - INFO - The previous best checkpoint /mnt/lustre/daiwenxun/X/mmaction2/work_dirs/swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb/best_acc/top1_epoch_13.pth is removed
2022/08/02 06:38:47 - mmengine - INFO - The best checkpoint with 0.7098 acc/top1 at 16 epoch is saved to best_acc/top1_epoch_16.pth.
2022/08/02 06:39:59 - mmengine - INFO - Epoch(train) [16][100/3757]  lr: 5.0002e-05  eta: 10:54:55  time: 0.6967  data_time: 0.0163  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.3746  loss: 1.3746
2022/08/02 06:41:08 - mmengine - INFO - Epoch(train) [16][200/3757]  lr: 5.0002e-05  eta: 10:53:45  time: 0.7011  data_time: 0.0161  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.5709  loss: 1.5709
2022/08/02 06:42:18 - mmengine - INFO - Epoch(train) [16][300/3757]  lr: 5.0002e-05  eta: 10:52:35  time: 0.6970  data_time: 0.0150  memory: 45143  top1_acc: 0.3750  top5_acc: 0.7500  loss_cls: 1.5711  loss: 1.5711
2022/08/02 06:43:35 - mmengine - INFO - Epoch(train) [16][400/3757]  lr: 5.0002e-05  eta: 10:51:32  time: 0.6950  data_time: 0.0154  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.4503  loss: 1.4503
2022/08/02 06:44:45 - mmengine - INFO - Epoch(train) [16][500/3757]  lr: 5.0002e-05  eta: 10:50:22  time: 0.7185  data_time: 0.0159  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.2669  loss: 1.2669
2022/08/02 06:45:55 - mmengine - INFO - Epoch(train) [16][600/3757]  lr: 5.0002e-05  eta: 10:49:13  time: 0.6928  data_time: 0.0162  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.4509  loss: 1.4509
2022/08/02 06:46:27 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 06:47:05 - mmengine - INFO - Epoch(train) [16][700/3757]  lr: 5.0002e-05  eta: 10:48:03  time: 0.7048  data_time: 0.0150  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.6269  loss: 1.6269
2022/08/02 06:48:16 - mmengine - INFO - Epoch(train) [16][800/3757]  lr: 5.0002e-05  eta: 10:46:53  time: 0.6923  data_time: 0.0162  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 1.4772  loss: 1.4772
2022/08/02 06:49:26 - mmengine - INFO - Epoch(train) [16][900/3757]  lr: 5.0002e-05  eta: 10:45:44  time: 0.6926  data_time: 0.0157  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.2075  loss: 1.2075
2022/08/02 06:50:36 - mmengine - INFO - Epoch(train) [16][1000/3757]  lr: 5.0002e-05  eta: 10:44:34  time: 0.6916  data_time: 0.0145  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.2750  loss: 1.2750
2022/08/02 06:51:46 - mmengine - INFO - Epoch(train) [16][1100/3757]  lr: 5.0002e-05  eta: 10:43:25  time: 0.6965  data_time: 0.0169  memory: 45143  top1_acc: 0.5000  top5_acc: 1.0000  loss_cls: 1.1035  loss: 1.1035
2022/08/02 06:52:56 - mmengine - INFO - Epoch(train) [16][1200/3757]  lr: 5.0002e-05  eta: 10:42:15  time: 0.6924  data_time: 0.0160  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 1.3009  loss: 1.3009
2022/08/02 06:54:06 - mmengine - INFO - Epoch(train) [16][1300/3757]  lr: 5.0002e-05  eta: 10:41:05  time: 0.6945  data_time: 0.0176  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 1.2637  loss: 1.2637
2022/08/02 06:55:16 - mmengine - INFO - Epoch(train) [16][1400/3757]  lr: 5.0002e-05  eta: 10:39:55  time: 0.6936  data_time: 0.0151  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.4106  loss: 1.4106
2022/08/02 06:56:26 - mmengine - INFO - Epoch(train) [16][1500/3757]  lr: 5.0002e-05  eta: 10:38:45  time: 0.7000  data_time: 0.0160  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.1621  loss: 1.1621
2022/08/02 06:57:35 - mmengine - INFO - Epoch(train) [16][1600/3757]  lr: 5.0002e-05  eta: 10:37:35  time: 0.6927  data_time: 0.0160  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.4645  loss: 1.4645
2022/08/02 06:58:07 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 06:58:45 - mmengine - INFO - Epoch(train) [16][1700/3757]  lr: 5.0002e-05  eta: 10:36:25  time: 0.6997  data_time: 0.0161  memory: 45143  top1_acc: 0.7500  top5_acc: 0.7500  loss_cls: 1.3812  loss: 1.3812
2022/08/02 06:59:55 - mmengine - INFO - Epoch(train) [16][1800/3757]  lr: 5.0002e-05  eta: 10:35:15  time: 0.7069  data_time: 0.0158  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 1.5669  loss: 1.5669
2022/08/02 07:01:04 - mmengine - INFO - Epoch(train) [16][1900/3757]  lr: 5.0002e-05  eta: 10:34:05  time: 0.6962  data_time: 0.0170  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.4225  loss: 1.4225
2022/08/02 07:02:14 - mmengine - INFO - Epoch(train) [16][2000/3757]  lr: 5.0002e-05  eta: 10:32:54  time: 0.6964  data_time: 0.0161  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 1.4625  loss: 1.4625
2022/08/02 07:03:24 - mmengine - INFO - Epoch(train) [16][2100/3757]  lr: 5.0002e-05  eta: 10:31:45  time: 0.6932  data_time: 0.0165  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 1.2033  loss: 1.2033
2022/08/02 07:04:33 - mmengine - INFO - Epoch(train) [16][2200/3757]  lr: 5.0002e-05  eta: 10:30:35  time: 0.7024  data_time: 0.0169  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.2673  loss: 1.2673
2022/08/02 07:05:43 - mmengine - INFO - Epoch(train) [16][2300/3757]  lr: 5.0002e-05  eta: 10:29:25  time: 0.7033  data_time: 0.0161  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 1.1778  loss: 1.1778
2022/08/02 07:06:53 - mmengine - INFO - Epoch(train) [16][2400/3757]  lr: 5.0002e-05  eta: 10:28:15  time: 0.6931  data_time: 0.0166  memory: 45143  top1_acc: 1.0000  top5_acc: 1.0000  loss_cls: 1.4531  loss: 1.4531
2022/08/02 07:08:03 - mmengine - INFO - Epoch(train) [16][2500/3757]  lr: 5.0002e-05  eta: 10:27:05  time: 0.7035  data_time: 0.0167  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.1852  loss: 1.1852
2022/08/02 07:09:12 - mmengine - INFO - Epoch(train) [16][2600/3757]  lr: 5.0002e-05  eta: 10:25:54  time: 0.6929  data_time: 0.0152  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 1.2579  loss: 1.2579
2022/08/02 07:09:44 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 07:10:22 - mmengine - INFO - Epoch(train) [16][2700/3757]  lr: 5.0002e-05  eta: 10:24:44  time: 0.6924  data_time: 0.0147  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 1.3512  loss: 1.3512
2022/08/02 07:11:31 - mmengine - INFO - Epoch(train) [16][2800/3757]  lr: 5.0002e-05  eta: 10:23:34  time: 0.6943  data_time: 0.0161  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 1.2603  loss: 1.2603
2022/08/02 07:12:41 - mmengine - INFO - Epoch(train) [16][2900/3757]  lr: 5.0002e-05  eta: 10:22:24  time: 0.6980  data_time: 0.0175  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 1.3428  loss: 1.3428
2022/08/02 07:13:50 - mmengine - INFO - Epoch(train) [16][3000/3757]  lr: 5.0002e-05  eta: 10:21:14  time: 0.6933  data_time: 0.0148  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.3007  loss: 1.3007
2022/08/02 07:15:00 - mmengine - INFO - Epoch(train) [16][3100/3757]  lr: 5.0002e-05  eta: 10:20:04  time: 0.6907  data_time: 0.0151  memory: 45143  top1_acc: 1.0000  top5_acc: 1.0000  loss_cls: 1.1716  loss: 1.1716
2022/08/02 07:16:10 - mmengine - INFO - Epoch(train) [16][3200/3757]  lr: 5.0002e-05  eta: 10:18:54  time: 0.6924  data_time: 0.0159  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.2378  loss: 1.2378
2022/08/02 07:17:20 - mmengine - INFO - Epoch(train) [16][3300/3757]  lr: 5.0002e-05  eta: 10:17:44  time: 0.6945  data_time: 0.0151  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.3608  loss: 1.3608
2022/08/02 07:18:29 - mmengine - INFO - Epoch(train) [16][3400/3757]  lr: 5.0002e-05  eta: 10:16:34  time: 0.6937  data_time: 0.0157  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.4427  loss: 1.4427
2022/08/02 07:19:40 - mmengine - INFO - Epoch(train) [16][3500/3757]  lr: 5.0002e-05  eta: 10:15:25  time: 0.7053  data_time: 0.0150  memory: 45143  top1_acc: 1.0000  top5_acc: 1.0000  loss_cls: 1.0724  loss: 1.0724
2022/08/02 07:20:50 - mmengine - INFO - Epoch(train) [16][3600/3757]  lr: 5.0002e-05  eta: 10:14:15  time: 0.6970  data_time: 0.0152  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 1.5619  loss: 1.5619
2022/08/02 07:21:21 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 07:22:00 - mmengine - INFO - Epoch(train) [16][3700/3757]  lr: 5.0002e-05  eta: 10:13:05  time: 0.6932  data_time: 0.0145  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.4332  loss: 1.4332
2022/08/02 07:22:40 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 07:22:40 - mmengine - INFO - Epoch(train) [16][3757/3757]  lr: 5.0002e-05  eta: 10:12:37  time: 0.6900  data_time: 0.0146  memory: 45143  top1_acc: 0.5714  top5_acc: 0.8571  loss_cls: 1.2803  loss: 1.2803
2022/08/02 07:23:52 - mmengine - INFO - Epoch(train) [17][100/3757]  lr: 4.4776e-05  eta: 10:11:07  time: 0.6925  data_time: 0.0159  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.2638  loss: 1.2638
2022/08/02 07:25:02 - mmengine - INFO - Epoch(train) [17][200/3757]  lr: 4.4776e-05  eta: 10:09:57  time: 0.6905  data_time: 0.0149  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 1.0221  loss: 1.0221
2022/08/02 07:26:11 - mmengine - INFO - Epoch(train) [17][300/3757]  lr: 4.4776e-05  eta: 10:08:47  time: 0.6935  data_time: 0.0181  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.1798  loss: 1.1798
2022/08/02 07:27:21 - mmengine - INFO - Epoch(train) [17][400/3757]  lr: 4.4776e-05  eta: 10:07:37  time: 0.6914  data_time: 0.0144  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.2828  loss: 1.2828
2022/08/02 07:28:31 - mmengine - INFO - Epoch(train) [17][500/3757]  lr: 4.4776e-05  eta: 10:06:28  time: 0.6953  data_time: 0.0176  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.3172  loss: 1.3172
2022/08/02 07:29:42 - mmengine - INFO - Epoch(train) [17][600/3757]  lr: 4.4776e-05  eta: 10:05:18  time: 0.7021  data_time: 0.0156  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.1436  loss: 1.1436
2022/08/02 07:30:52 - mmengine - INFO - Epoch(train) [17][700/3757]  lr: 4.4776e-05  eta: 10:04:09  time: 0.6909  data_time: 0.0160  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.1177  loss: 1.1177
2022/08/02 07:32:01 - mmengine - INFO - Epoch(train) [17][800/3757]  lr: 4.4776e-05  eta: 10:02:58  time: 0.6905  data_time: 0.0154  memory: 45143  top1_acc: 0.3750  top5_acc: 0.8750  loss_cls: 1.0629  loss: 1.0629
2022/08/02 07:33:03 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 07:33:11 - mmengine - INFO - Epoch(train) [17][900/3757]  lr: 4.4776e-05  eta: 10:01:49  time: 0.6913  data_time: 0.0162  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.2769  loss: 1.2769
2022/08/02 07:34:21 - mmengine - INFO - Epoch(train) [17][1000/3757]  lr: 4.4776e-05  eta: 10:00:39  time: 0.7013  data_time: 0.0155  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 1.3758  loss: 1.3758
2022/08/02 07:35:31 - mmengine - INFO - Epoch(train) [17][1100/3757]  lr: 4.4776e-05  eta: 9:59:29  time: 0.6928  data_time: 0.0161  memory: 45143  top1_acc: 0.7500  top5_acc: 0.7500  loss_cls: 1.2427  loss: 1.2427
2022/08/02 07:36:42 - mmengine - INFO - Epoch(train) [17][1200/3757]  lr: 4.4776e-05  eta: 9:58:20  time: 0.7153  data_time: 0.0157  memory: 45143  top1_acc: 0.6250  top5_acc: 1.0000  loss_cls: 1.4837  loss: 1.4837
2022/08/02 07:37:51 - mmengine - INFO - Epoch(train) [17][1300/3757]  lr: 4.4776e-05  eta: 9:57:10  time: 0.6915  data_time: 0.0160  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.2769  loss: 1.2769
2022/08/02 07:39:01 - mmengine - INFO - Epoch(train) [17][1400/3757]  lr: 4.4776e-05  eta: 9:56:00  time: 0.6963  data_time: 0.0151  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.1442  loss: 1.1442
2022/08/02 07:40:11 - mmengine - INFO - Epoch(train) [17][1500/3757]  lr: 4.4776e-05  eta: 9:54:50  time: 0.6921  data_time: 0.0163  memory: 45143  top1_acc: 1.0000  top5_acc: 1.0000  loss_cls: 1.5006  loss: 1.5006
2022/08/02 07:41:21 - mmengine - INFO - Epoch(train) [17][1600/3757]  lr: 4.4776e-05  eta: 9:53:40  time: 0.7003  data_time: 0.0160  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 1.2924  loss: 1.2924
2022/08/02 07:42:31 - mmengine - INFO - Epoch(train) [17][1700/3757]  lr: 4.4776e-05  eta: 9:52:30  time: 0.6922  data_time: 0.0155  memory: 45143  top1_acc: 0.3750  top5_acc: 0.8750  loss_cls: 1.4705  loss: 1.4705
2022/08/02 07:43:41 - mmengine - INFO - Epoch(train) [17][1800/3757]  lr: 4.4776e-05  eta: 9:51:21  time: 0.6919  data_time: 0.0156  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 1.4619  loss: 1.4619
2022/08/02 07:44:43 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 07:44:51 - mmengine - INFO - Epoch(train) [17][1900/3757]  lr: 4.4776e-05  eta: 9:50:11  time: 0.6908  data_time: 0.0146  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.4480  loss: 1.4480
2022/08/02 07:46:01 - mmengine - INFO - Epoch(train) [17][2000/3757]  lr: 4.4776e-05  eta: 9:49:01  time: 0.7005  data_time: 0.0164  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.2491  loss: 1.2491
2022/08/02 07:47:11 - mmengine - INFO - Epoch(train) [17][2100/3757]  lr: 4.4776e-05  eta: 9:47:51  time: 0.6909  data_time: 0.0155  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 1.2196  loss: 1.2196
2022/08/02 07:48:21 - mmengine - INFO - Epoch(train) [17][2200/3757]  lr: 4.4776e-05  eta: 9:46:42  time: 0.7040  data_time: 0.0168  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 1.2481  loss: 1.2481
2022/08/02 07:49:31 - mmengine - INFO - Epoch(train) [17][2300/3757]  lr: 4.4776e-05  eta: 9:45:32  time: 0.6886  data_time: 0.0149  memory: 45143  top1_acc: 1.0000  top5_acc: 1.0000  loss_cls: 1.1593  loss: 1.1593
2022/08/02 07:50:42 - mmengine - INFO - Epoch(train) [17][2400/3757]  lr: 4.4776e-05  eta: 9:44:23  time: 0.6958  data_time: 0.0154  memory: 45143  top1_acc: 0.7500  top5_acc: 0.7500  loss_cls: 1.3365  loss: 1.3365
2022/08/02 07:51:52 - mmengine - INFO - Epoch(train) [17][2500/3757]  lr: 4.4776e-05  eta: 9:43:14  time: 0.6927  data_time: 0.0156  memory: 45143  top1_acc: 0.2500  top5_acc: 0.6250  loss_cls: 1.6026  loss: 1.6026
2022/08/02 07:53:03 - mmengine - INFO - Epoch(train) [17][2600/3757]  lr: 4.4776e-05  eta: 9:42:04  time: 0.6989  data_time: 0.0152  memory: 45143  top1_acc: 0.5000  top5_acc: 0.6250  loss_cls: 1.1866  loss: 1.1866
2022/08/02 07:54:12 - mmengine - INFO - Epoch(train) [17][2700/3757]  lr: 4.4776e-05  eta: 9:40:54  time: 0.6914  data_time: 0.0155  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.0511  loss: 1.0511
2022/08/02 07:55:22 - mmengine - INFO - Epoch(train) [17][2800/3757]  lr: 4.4776e-05  eta: 9:39:44  time: 0.6934  data_time: 0.0151  memory: 45143  top1_acc: 0.7500  top5_acc: 0.7500  loss_cls: 1.3971  loss: 1.3971
2022/08/02 07:56:23 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 07:56:32 - mmengine - INFO - Epoch(train) [17][2900/3757]  lr: 4.4776e-05  eta: 9:38:34  time: 0.6933  data_time: 0.0177  memory: 45143  top1_acc: 0.6250  top5_acc: 1.0000  loss_cls: 1.4347  loss: 1.4347
2022/08/02 07:57:41 - mmengine - INFO - Epoch(train) [17][3000/3757]  lr: 4.4776e-05  eta: 9:37:24  time: 0.6932  data_time: 0.0157  memory: 45143  top1_acc: 1.0000  top5_acc: 1.0000  loss_cls: 1.5199  loss: 1.5199
2022/08/02 07:58:51 - mmengine - INFO - Epoch(train) [17][3100/3757]  lr: 4.4776e-05  eta: 9:36:14  time: 0.6938  data_time: 0.0167  memory: 45143  top1_acc: 0.5000  top5_acc: 0.8750  loss_cls: 1.5666  loss: 1.5666
2022/08/02 08:00:01 - mmengine - INFO - Epoch(train) [17][3200/3757]  lr: 4.4776e-05  eta: 9:35:04  time: 0.7016  data_time: 0.0166  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 1.1663  loss: 1.1663
2022/08/02 08:01:11 - mmengine - INFO - Epoch(train) [17][3300/3757]  lr: 4.4776e-05  eta: 9:33:55  time: 0.7021  data_time: 0.0170  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.2598  loss: 1.2598
2022/08/02 08:02:21 - mmengine - INFO - Epoch(train) [17][3400/3757]  lr: 4.4776e-05  eta: 9:32:45  time: 0.7047  data_time: 0.0195  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.1299  loss: 1.1299
2022/08/02 08:03:31 - mmengine - INFO - Epoch(train) [17][3500/3757]  lr: 4.4776e-05  eta: 9:31:35  time: 0.7005  data_time: 0.0173  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.1862  loss: 1.1862
2022/08/02 08:04:42 - mmengine - INFO - Epoch(train) [17][3600/3757]  lr: 4.4776e-05  eta: 9:30:26  time: 0.7065  data_time: 0.0170  memory: 45143  top1_acc: 0.3750  top5_acc: 0.5000  loss_cls: 1.2919  loss: 1.2919
2022/08/02 08:05:51 - mmengine - INFO - Epoch(train) [17][3700/3757]  lr: 4.4776e-05  eta: 9:29:16  time: 0.6949  data_time: 0.0162  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.2073  loss: 1.2073
2022/08/02 08:06:31 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 08:06:31 - mmengine - INFO - Epoch(train) [17][3757/3757]  lr: 4.4776e-05  eta: 9:28:48  time: 0.6865  data_time: 0.0165  memory: 45143  top1_acc: 0.7143  top5_acc: 1.0000  loss_cls: 1.1229  loss: 1.1229
2022/08/02 08:07:43 - mmengine - INFO - Epoch(train) [18][100/3757]  lr: 3.9606e-05  eta: 9:27:19  time: 0.7058  data_time: 0.0167  memory: 45143  top1_acc: 0.7500  top5_acc: 0.7500  loss_cls: 1.2201  loss: 1.2201
2022/08/02 08:08:04 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 08:08:52 - mmengine - INFO - Epoch(train) [18][200/3757]  lr: 3.9606e-05  eta: 9:26:09  time: 0.6911  data_time: 0.0149  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.1160  loss: 1.1160
2022/08/02 08:10:02 - mmengine - INFO - Epoch(train) [18][300/3757]  lr: 3.9606e-05  eta: 9:24:59  time: 0.7023  data_time: 0.0171  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.3958  loss: 1.3958
2022/08/02 08:11:12 - mmengine - INFO - Epoch(train) [18][400/3757]  lr: 3.9606e-05  eta: 9:23:49  time: 0.6987  data_time: 0.0164  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.3813  loss: 1.3813
2022/08/02 08:12:21 - mmengine - INFO - Epoch(train) [18][500/3757]  lr: 3.9606e-05  eta: 9:22:39  time: 0.6927  data_time: 0.0158  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.2575  loss: 1.2575
2022/08/02 08:13:31 - mmengine - INFO - Epoch(train) [18][600/3757]  lr: 3.9606e-05  eta: 9:21:29  time: 0.6992  data_time: 0.0162  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 1.4720  loss: 1.4720
2022/08/02 08:14:41 - mmengine - INFO - Epoch(train) [18][700/3757]  lr: 3.9606e-05  eta: 9:20:19  time: 0.7073  data_time: 0.0167  memory: 45143  top1_acc: 0.5000  top5_acc: 0.8750  loss_cls: 1.5663  loss: 1.5663
2022/08/02 08:15:51 - mmengine - INFO - Epoch(train) [18][800/3757]  lr: 3.9606e-05  eta: 9:19:09  time: 0.6975  data_time: 0.0167  memory: 45143  top1_acc: 0.6250  top5_acc: 1.0000  loss_cls: 1.1294  loss: 1.1294
2022/08/02 08:17:02 - mmengine - INFO - Epoch(train) [18][900/3757]  lr: 3.9606e-05  eta: 9:18:00  time: 0.7075  data_time: 0.0165  memory: 45143  top1_acc: 0.7500  top5_acc: 0.7500  loss_cls: 1.5040  loss: 1.5040
2022/08/02 08:18:12 - mmengine - INFO - Epoch(train) [18][1000/3757]  lr: 3.9606e-05  eta: 9:16:51  time: 0.7153  data_time: 0.0172  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.3364  loss: 1.3364
2022/08/02 08:19:23 - mmengine - INFO - Epoch(train) [18][1100/3757]  lr: 3.9606e-05  eta: 9:15:41  time: 0.7083  data_time: 0.0174  memory: 45143  top1_acc: 0.3750  top5_acc: 0.8750  loss_cls: 1.1782  loss: 1.1782
2022/08/02 08:19:45 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 08:20:33 - mmengine - INFO - Epoch(train) [18][1200/3757]  lr: 3.9606e-05  eta: 9:14:32  time: 0.7030  data_time: 0.0181  memory: 45143  top1_acc: 0.2500  top5_acc: 0.8750  loss_cls: 1.1684  loss: 1.1684
2022/08/02 08:21:43 - mmengine - INFO - Epoch(train) [18][1300/3757]  lr: 3.9606e-05  eta: 9:13:22  time: 0.7038  data_time: 0.0167  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.2964  loss: 1.2964
2022/08/02 08:22:53 - mmengine - INFO - Epoch(train) [18][1400/3757]  lr: 3.9606e-05  eta: 9:12:12  time: 0.6932  data_time: 0.0171  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 1.2041  loss: 1.2041
2022/08/02 08:24:04 - mmengine - INFO - Epoch(train) [18][1500/3757]  lr: 3.9606e-05  eta: 9:11:03  time: 0.7069  data_time: 0.0169  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.3294  loss: 1.3294
2022/08/02 08:25:14 - mmengine - INFO - Epoch(train) [18][1600/3757]  lr: 3.9606e-05  eta: 9:09:53  time: 0.6935  data_time: 0.0157  memory: 45143  top1_acc: 1.0000  top5_acc: 1.0000  loss_cls: 1.2527  loss: 1.2527
2022/08/02 08:26:23 - mmengine - INFO - Epoch(train) [18][1700/3757]  lr: 3.9606e-05  eta: 9:08:43  time: 0.6977  data_time: 0.0155  memory: 45143  top1_acc: 0.7500  top5_acc: 0.7500  loss_cls: 1.3934  loss: 1.3934
2022/08/02 08:27:34 - mmengine - INFO - Epoch(train) [18][1800/3757]  lr: 3.9606e-05  eta: 9:07:34  time: 0.6985  data_time: 0.0171  memory: 45143  top1_acc: 1.0000  top5_acc: 1.0000  loss_cls: 1.0673  loss: 1.0673
2022/08/02 08:28:43 - mmengine - INFO - Epoch(train) [18][1900/3757]  lr: 3.9606e-05  eta: 9:06:24  time: 0.6962  data_time: 0.0160  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.1697  loss: 1.1697
2022/08/02 08:29:53 - mmengine - INFO - Epoch(train) [18][2000/3757]  lr: 3.9606e-05  eta: 9:05:14  time: 0.7190  data_time: 0.0167  memory: 45143  top1_acc: 1.0000  top5_acc: 1.0000  loss_cls: 0.9618  loss: 0.9618
2022/08/02 08:31:03 - mmengine - INFO - Epoch(train) [18][2100/3757]  lr: 3.9606e-05  eta: 9:04:04  time: 0.7020  data_time: 0.0171  memory: 45143  top1_acc: 0.5000  top5_acc: 1.0000  loss_cls: 1.3842  loss: 1.3842
2022/08/02 08:31:25 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 08:32:13 - mmengine - INFO - Epoch(train) [18][2200/3757]  lr: 3.9606e-05  eta: 9:02:54  time: 0.6956  data_time: 0.0176  memory: 45143  top1_acc: 1.0000  top5_acc: 1.0000  loss_cls: 1.2200  loss: 1.2200
2022/08/02 08:33:23 - mmengine - INFO - Epoch(train) [18][2300/3757]  lr: 3.9606e-05  eta: 9:01:45  time: 0.6972  data_time: 0.0175  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 1.1674  loss: 1.1674
2022/08/02 08:34:33 - mmengine - INFO - Epoch(train) [18][2400/3757]  lr: 3.9606e-05  eta: 9:00:35  time: 0.6972  data_time: 0.0162  memory: 45143  top1_acc: 0.2500  top5_acc: 0.7500  loss_cls: 1.3485  loss: 1.3485
2022/08/02 08:35:43 - mmengine - INFO - Epoch(train) [18][2500/3757]  lr: 3.9606e-05  eta: 8:59:25  time: 0.7115  data_time: 0.0171  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.1793  loss: 1.1793
2022/08/02 08:36:53 - mmengine - INFO - Epoch(train) [18][2600/3757]  lr: 3.9606e-05  eta: 8:58:15  time: 0.7055  data_time: 0.0162  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.0048  loss: 1.0048
2022/08/02 08:38:03 - mmengine - INFO - Epoch(train) [18][2700/3757]  lr: 3.9606e-05  eta: 8:57:05  time: 0.7054  data_time: 0.0174  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 1.0861  loss: 1.0861
2022/08/02 08:39:13 - mmengine - INFO - Epoch(train) [18][2800/3757]  lr: 3.9606e-05  eta: 8:55:56  time: 0.7133  data_time: 0.0162  memory: 45143  top1_acc: 1.0000  top5_acc: 1.0000  loss_cls: 1.1862  loss: 1.1862
2022/08/02 08:40:23 - mmengine - INFO - Epoch(train) [18][2900/3757]  lr: 3.9606e-05  eta: 8:54:46  time: 0.6966  data_time: 0.0160  memory: 45143  top1_acc: 0.5000  top5_acc: 1.0000  loss_cls: 1.3165  loss: 1.3165
2022/08/02 08:41:33 - mmengine - INFO - Epoch(train) [18][3000/3757]  lr: 3.9606e-05  eta: 8:53:36  time: 0.6955  data_time: 0.0167  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 1.2621  loss: 1.2621
2022/08/02 08:42:43 - mmengine - INFO - Epoch(train) [18][3100/3757]  lr: 3.9606e-05  eta: 8:52:26  time: 0.6958  data_time: 0.0167  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 1.1108  loss: 1.1108
2022/08/02 08:43:05 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 08:43:53 - mmengine - INFO - Epoch(train) [18][3200/3757]  lr: 3.9606e-05  eta: 8:51:17  time: 0.7131  data_time: 0.0164  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.1624  loss: 1.1624
2022/08/02 08:45:03 - mmengine - INFO - Epoch(train) [18][3300/3757]  lr: 3.9606e-05  eta: 8:50:07  time: 0.7010  data_time: 0.0171  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.3319  loss: 1.3319
2022/08/02 08:46:13 - mmengine - INFO - Epoch(train) [18][3400/3757]  lr: 3.9606e-05  eta: 8:48:57  time: 0.7009  data_time: 0.0177  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 1.0732  loss: 1.0732
2022/08/02 08:47:23 - mmengine - INFO - Epoch(train) [18][3500/3757]  lr: 3.9606e-05  eta: 8:47:48  time: 0.6950  data_time: 0.0164  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.3423  loss: 1.3423
2022/08/02 08:48:33 - mmengine - INFO - Epoch(train) [18][3600/3757]  lr: 3.9606e-05  eta: 8:46:38  time: 0.7095  data_time: 0.0167  memory: 45143  top1_acc: 0.5000  top5_acc: 1.0000  loss_cls: 1.1155  loss: 1.1155
2022/08/02 08:49:43 - mmengine - INFO - Epoch(train) [18][3700/3757]  lr: 3.9606e-05  eta: 8:45:28  time: 0.6927  data_time: 0.0160  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.1636  loss: 1.1636
2022/08/02 08:50:23 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 08:50:23 - mmengine - INFO - Epoch(train) [18][3757/3757]  lr: 3.9606e-05  eta: 8:45:00  time: 0.7122  data_time: 0.0175  memory: 45143  top1_acc: 1.0000  top5_acc: 1.0000  loss_cls: 1.2631  loss: 1.2631
2022/08/02 08:50:24 - mmengine - INFO - Saving checkpoint at 18 epochs
2022/08/02 08:51:00 - mmengine - INFO - Epoch(val) [18][100/310]    eta: 0:00:57  time: 0.2723  data_time: 0.0126  memory: 8742  
2022/08/02 08:51:27 - mmengine - INFO - Epoch(val) [18][200/310]    eta: 0:00:32  time: 0.2910  data_time: 0.0181  memory: 8742  
2022/08/02 08:51:54 - mmengine - INFO - Epoch(val) [18][300/310]    eta: 0:00:02  time: 0.2600  data_time: 0.0086  memory: 8742  
2022/08/02 08:51:58 - mmengine - INFO - Epoch(val) [18][310/310]  acc/top1: 0.7328  acc/top5: 0.9066  acc/mean1: 0.7327
2022/08/02 08:51:58 - mmengine - INFO - The previous best checkpoint /mnt/lustre/daiwenxun/X/mmaction2/work_dirs/swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb/best_acc/top1_epoch_16.pth is removed
2022/08/02 08:52:01 - mmengine - INFO - The best checkpoint with 0.7328 acc/top1 at 19 epoch is saved to best_acc/top1_epoch_19.pth.
2022/08/02 08:53:12 - mmengine - INFO - Epoch(train) [19][100/3757]  lr: 3.4551e-05  eta: 8:43:31  time: 0.6914  data_time: 0.0168  memory: 45143  top1_acc: 0.7500  top5_acc: 0.7500  loss_cls: 1.1827  loss: 1.1827
2022/08/02 08:54:22 - mmengine - INFO - Epoch(train) [19][200/3757]  lr: 3.4551e-05  eta: 8:42:21  time: 0.6916  data_time: 0.0149  memory: 45143  top1_acc: 0.6250  top5_acc: 1.0000  loss_cls: 1.2026  loss: 1.2026
2022/08/02 08:55:32 - mmengine - INFO - Epoch(train) [19][300/3757]  lr: 3.4551e-05  eta: 8:41:12  time: 0.6943  data_time: 0.0169  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.1015  loss: 1.1015
2022/08/02 08:56:23 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 08:56:42 - mmengine - INFO - Epoch(train) [19][400/3757]  lr: 3.4551e-05  eta: 8:40:02  time: 0.7040  data_time: 0.0157  memory: 45143  top1_acc: 0.5000  top5_acc: 1.0000  loss_cls: 1.3946  loss: 1.3946
2022/08/02 08:57:51 - mmengine - INFO - Epoch(train) [19][500/3757]  lr: 3.4551e-05  eta: 8:38:52  time: 0.6951  data_time: 0.0161  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 1.0911  loss: 1.0911
2022/08/02 08:59:01 - mmengine - INFO - Epoch(train) [19][600/3757]  lr: 3.4551e-05  eta: 8:37:42  time: 0.6900  data_time: 0.0152  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 0.8928  loss: 0.8928
2022/08/02 09:00:11 - mmengine - INFO - Epoch(train) [19][700/3757]  lr: 3.4551e-05  eta: 8:36:32  time: 0.6930  data_time: 0.0159  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.2680  loss: 1.2680
2022/08/02 09:01:20 - mmengine - INFO - Epoch(train) [19][800/3757]  lr: 3.4551e-05  eta: 8:35:22  time: 0.6916  data_time: 0.0145  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 1.1634  loss: 1.1634
2022/08/02 09:02:30 - mmengine - INFO - Epoch(train) [19][900/3757]  lr: 3.4551e-05  eta: 8:34:12  time: 0.6957  data_time: 0.0162  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.4127  loss: 1.4127
2022/08/02 09:03:39 - mmengine - INFO - Epoch(train) [19][1000/3757]  lr: 3.4551e-05  eta: 8:33:02  time: 0.6942  data_time: 0.0152  memory: 45143  top1_acc: 0.5000  top5_acc: 0.8750  loss_cls: 1.2158  loss: 1.2158
2022/08/02 09:04:49 - mmengine - INFO - Epoch(train) [19][1100/3757]  lr: 3.4551e-05  eta: 8:31:52  time: 0.6910  data_time: 0.0163  memory: 45143  top1_acc: 0.3750  top5_acc: 0.7500  loss_cls: 1.5240  loss: 1.5240
2022/08/02 09:05:59 - mmengine - INFO - Epoch(train) [19][1200/3757]  lr: 3.4551e-05  eta: 8:30:42  time: 0.6919  data_time: 0.0157  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 1.4097  loss: 1.4097
2022/08/02 09:07:08 - mmengine - INFO - Epoch(train) [19][1300/3757]  lr: 3.4551e-05  eta: 8:29:32  time: 0.6942  data_time: 0.0164  memory: 45143  top1_acc: 0.7500  top5_acc: 0.7500  loss_cls: 1.1579  loss: 1.1579
2022/08/02 09:08:00 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 09:08:18 - mmengine - INFO - Epoch(train) [19][1400/3757]  lr: 3.4551e-05  eta: 8:28:22  time: 0.6914  data_time: 0.0158  memory: 45143  top1_acc: 0.7500  top5_acc: 0.7500  loss_cls: 1.2709  loss: 1.2709
2022/08/02 09:09:27 - mmengine - INFO - Epoch(train) [19][1500/3757]  lr: 3.4551e-05  eta: 8:27:12  time: 0.7006  data_time: 0.0167  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.3698  loss: 1.3698
2022/08/02 09:10:37 - mmengine - INFO - Epoch(train) [19][1600/3757]  lr: 3.4551e-05  eta: 8:26:02  time: 0.6976  data_time: 0.0165  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.0902  loss: 1.0902
2022/08/02 09:11:47 - mmengine - INFO - Epoch(train) [19][1700/3757]  lr: 3.4551e-05  eta: 8:24:52  time: 0.7014  data_time: 0.0160  memory: 45143  top1_acc: 0.3750  top5_acc: 0.6250  loss_cls: 1.3236  loss: 1.3236
2022/08/02 09:12:57 - mmengine - INFO - Epoch(train) [19][1800/3757]  lr: 3.4551e-05  eta: 8:23:42  time: 0.6971  data_time: 0.0162  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.2791  loss: 1.2791
2022/08/02 09:14:06 - mmengine - INFO - Epoch(train) [19][1900/3757]  lr: 3.4551e-05  eta: 8:22:32  time: 0.6970  data_time: 0.0160  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 0.8715  loss: 0.8715
2022/08/02 09:15:16 - mmengine - INFO - Epoch(train) [19][2000/3757]  lr: 3.4551e-05  eta: 8:21:22  time: 0.6981  data_time: 0.0158  memory: 45143  top1_acc: 0.6250  top5_acc: 1.0000  loss_cls: 1.2712  loss: 1.2712
2022/08/02 09:16:26 - mmengine - INFO - Epoch(train) [19][2100/3757]  lr: 3.4551e-05  eta: 8:20:13  time: 0.6994  data_time: 0.0161  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.2587  loss: 1.2587
2022/08/02 09:17:36 - mmengine - INFO - Epoch(train) [19][2200/3757]  lr: 3.4551e-05  eta: 8:19:03  time: 0.6963  data_time: 0.0157  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.1057  loss: 1.1057
2022/08/02 09:18:46 - mmengine - INFO - Epoch(train) [19][2300/3757]  lr: 3.4551e-05  eta: 8:17:53  time: 0.6997  data_time: 0.0161  memory: 45143  top1_acc: 0.2500  top5_acc: 0.8750  loss_cls: 1.2156  loss: 1.2156
2022/08/02 09:19:38 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 09:19:56 - mmengine - INFO - Epoch(train) [19][2400/3757]  lr: 3.4551e-05  eta: 8:16:44  time: 0.7001  data_time: 0.0166  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.0274  loss: 1.0274
2022/08/02 09:21:06 - mmengine - INFO - Epoch(train) [19][2500/3757]  lr: 3.4551e-05  eta: 8:15:34  time: 0.7017  data_time: 0.0156  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.2017  loss: 1.2017
2022/08/02 09:22:15 - mmengine - INFO - Epoch(train) [19][2600/3757]  lr: 3.4551e-05  eta: 8:14:24  time: 0.6951  data_time: 0.0151  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 1.0188  loss: 1.0188
2022/08/02 09:23:25 - mmengine - INFO - Epoch(train) [19][2700/3757]  lr: 3.4551e-05  eta: 8:13:14  time: 0.6978  data_time: 0.0160  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 1.0245  loss: 1.0245
2022/08/02 09:24:35 - mmengine - INFO - Epoch(train) [19][2800/3757]  lr: 3.4551e-05  eta: 8:12:04  time: 0.6918  data_time: 0.0159  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 0.9156  loss: 0.9156
2022/08/02 09:25:45 - mmengine - INFO - Epoch(train) [19][2900/3757]  lr: 3.4551e-05  eta: 8:10:54  time: 0.6955  data_time: 0.0155  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.2269  loss: 1.2269
2022/08/02 09:26:54 - mmengine - INFO - Epoch(train) [19][3000/3757]  lr: 3.4551e-05  eta: 8:09:44  time: 0.6913  data_time: 0.0148  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.2146  loss: 1.2146
2022/08/02 09:28:04 - mmengine - INFO - Epoch(train) [19][3100/3757]  lr: 3.4551e-05  eta: 8:08:34  time: 0.6944  data_time: 0.0163  memory: 45143  top1_acc: 0.3750  top5_acc: 0.7500  loss_cls: 1.2571  loss: 1.2571
2022/08/02 09:29:14 - mmengine - INFO - Epoch(train) [19][3200/3757]  lr: 3.4551e-05  eta: 8:07:24  time: 0.6930  data_time: 0.0154  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.5321  loss: 1.5321
2022/08/02 09:30:24 - mmengine - INFO - Epoch(train) [19][3300/3757]  lr: 3.4551e-05  eta: 8:06:15  time: 0.7020  data_time: 0.0151  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.1281  loss: 1.1281
2022/08/02 09:31:15 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 09:31:34 - mmengine - INFO - Epoch(train) [19][3400/3757]  lr: 3.4551e-05  eta: 8:05:05  time: 0.6926  data_time: 0.0156  memory: 45143  top1_acc: 0.6250  top5_acc: 1.0000  loss_cls: 1.1218  loss: 1.1218
2022/08/02 09:32:44 - mmengine - INFO - Epoch(train) [19][3500/3757]  lr: 3.4551e-05  eta: 8:03:55  time: 0.6950  data_time: 0.0162  memory: 45143  top1_acc: 0.5000  top5_acc: 0.6250  loss_cls: 0.8649  loss: 0.8649
2022/08/02 09:33:53 - mmengine - INFO - Epoch(train) [19][3600/3757]  lr: 3.4551e-05  eta: 8:02:45  time: 0.6923  data_time: 0.0147  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 1.0148  loss: 1.0148
2022/08/02 09:35:04 - mmengine - INFO - Epoch(train) [19][3700/3757]  lr: 3.4551e-05  eta: 8:01:36  time: 0.6951  data_time: 0.0164  memory: 45143  top1_acc: 0.7500  top5_acc: 0.7500  loss_cls: 1.4761  loss: 1.4761
2022/08/02 09:35:43 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 09:35:43 - mmengine - INFO - Epoch(train) [19][3757/3757]  lr: 3.4551e-05  eta: 8:01:08  time: 0.6896  data_time: 0.0164  memory: 45143  top1_acc: 0.7143  top5_acc: 0.8571  loss_cls: 1.3380  loss: 1.3380
2022/08/02 09:36:56 - mmengine - INFO - Epoch(train) [20][100/3757]  lr: 2.9665e-05  eta: 7:59:41  time: 0.6898  data_time: 0.0149  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 1.0405  loss: 1.0405
2022/08/02 09:38:06 - mmengine - INFO - Epoch(train) [20][200/3757]  lr: 2.9665e-05  eta: 7:58:31  time: 0.7051  data_time: 0.0159  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 1.0028  loss: 1.0028
2022/08/02 09:39:16 - mmengine - INFO - Epoch(train) [20][300/3757]  lr: 2.9665e-05  eta: 7:57:21  time: 0.6923  data_time: 0.0155  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 1.0192  loss: 1.0192
2022/08/02 09:40:25 - mmengine - INFO - Epoch(train) [20][400/3757]  lr: 2.9665e-05  eta: 7:56:11  time: 0.6930  data_time: 0.0174  memory: 45143  top1_acc: 0.3750  top5_acc: 0.7500  loss_cls: 1.2583  loss: 1.2583
2022/08/02 09:41:35 - mmengine - INFO - Epoch(train) [20][500/3757]  lr: 2.9665e-05  eta: 7:55:01  time: 0.6957  data_time: 0.0150  memory: 45143  top1_acc: 0.3750  top5_acc: 0.8750  loss_cls: 1.2679  loss: 1.2679
2022/08/02 09:42:45 - mmengine - INFO - Epoch(train) [20][600/3757]  lr: 2.9665e-05  eta: 7:53:52  time: 0.7077  data_time: 0.0158  memory: 45143  top1_acc: 0.6250  top5_acc: 1.0000  loss_cls: 1.3465  loss: 1.3465
2022/08/02 09:42:57 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 09:43:55 - mmengine - INFO - Epoch(train) [20][700/3757]  lr: 2.9665e-05  eta: 7:52:42  time: 0.6899  data_time: 0.0148  memory: 45143  top1_acc: 0.7500  top5_acc: 0.7500  loss_cls: 1.2387  loss: 1.2387
2022/08/02 09:45:05 - mmengine - INFO - Epoch(train) [20][800/3757]  lr: 2.9665e-05  eta: 7:51:32  time: 0.7033  data_time: 0.0163  memory: 45143  top1_acc: 0.7500  top5_acc: 0.7500  loss_cls: 1.0077  loss: 1.0077
2022/08/02 09:46:15 - mmengine - INFO - Epoch(train) [20][900/3757]  lr: 2.9665e-05  eta: 7:50:22  time: 0.6940  data_time: 0.0154  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.0670  loss: 1.0670
2022/08/02 09:47:25 - mmengine - INFO - Epoch(train) [20][1000/3757]  lr: 2.9665e-05  eta: 7:49:13  time: 0.6991  data_time: 0.0167  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 0.9067  loss: 0.9067
2022/08/02 09:48:35 - mmengine - INFO - Epoch(train) [20][1100/3757]  lr: 2.9665e-05  eta: 7:48:03  time: 0.6916  data_time: 0.0162  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.0010  loss: 1.0010
2022/08/02 09:49:45 - mmengine - INFO - Epoch(train) [20][1200/3757]  lr: 2.9665e-05  eta: 7:46:53  time: 0.7037  data_time: 0.0163  memory: 45143  top1_acc: 0.6250  top5_acc: 1.0000  loss_cls: 1.2256  loss: 1.2256
2022/08/02 09:50:54 - mmengine - INFO - Epoch(train) [20][1300/3757]  lr: 2.9665e-05  eta: 7:45:43  time: 0.6909  data_time: 0.0154  memory: 45143  top1_acc: 1.0000  top5_acc: 1.0000  loss_cls: 1.0011  loss: 1.0011
2022/08/02 09:52:04 - mmengine - INFO - Epoch(train) [20][1400/3757]  lr: 2.9665e-05  eta: 7:44:33  time: 0.6993  data_time: 0.0160  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.2919  loss: 1.2919
2022/08/02 09:53:14 - mmengine - INFO - Epoch(train) [20][1500/3757]  lr: 2.9665e-05  eta: 7:43:23  time: 0.6899  data_time: 0.0148  memory: 45143  top1_acc: 1.0000  top5_acc: 1.0000  loss_cls: 1.1465  loss: 1.1465
2022/08/02 09:54:24 - mmengine - INFO - Epoch(train) [20][1600/3757]  lr: 2.9665e-05  eta: 7:42:14  time: 0.7131  data_time: 0.0157  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 1.1206  loss: 1.1206
2022/08/02 09:54:36 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 09:55:34 - mmengine - INFO - Epoch(train) [20][1700/3757]  lr: 2.9665e-05  eta: 7:41:04  time: 0.6922  data_time: 0.0159  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.2780  loss: 1.2780
2022/08/02 09:56:44 - mmengine - INFO - Epoch(train) [20][1800/3757]  lr: 2.9665e-05  eta: 7:39:54  time: 0.7109  data_time: 0.0165  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.0932  loss: 1.0932
2022/08/02 09:57:54 - mmengine - INFO - Epoch(train) [20][1900/3757]  lr: 2.9665e-05  eta: 7:38:45  time: 0.6946  data_time: 0.0147  memory: 45143  top1_acc: 0.5000  top5_acc: 1.0000  loss_cls: 1.2392  loss: 1.2392
2022/08/02 09:59:04 - mmengine - INFO - Epoch(train) [20][2000/3757]  lr: 2.9665e-05  eta: 7:37:35  time: 0.6941  data_time: 0.0167  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.2669  loss: 1.2669
2022/08/02 10:00:14 - mmengine - INFO - Epoch(train) [20][2100/3757]  lr: 2.9665e-05  eta: 7:36:25  time: 0.6899  data_time: 0.0148  memory: 45143  top1_acc: 0.5000  top5_acc: 0.6250  loss_cls: 1.2621  loss: 1.2621
2022/08/02 10:01:24 - mmengine - INFO - Epoch(train) [20][2200/3757]  lr: 2.9665e-05  eta: 7:35:15  time: 0.7049  data_time: 0.0169  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.1690  loss: 1.1690
2022/08/02 10:02:33 - mmengine - INFO - Epoch(train) [20][2300/3757]  lr: 2.9665e-05  eta: 7:34:05  time: 0.6901  data_time: 0.0146  memory: 45143  top1_acc: 0.7500  top5_acc: 0.7500  loss_cls: 1.0596  loss: 1.0596
2022/08/02 10:03:43 - mmengine - INFO - Epoch(train) [20][2400/3757]  lr: 2.9665e-05  eta: 7:32:56  time: 0.7014  data_time: 0.0176  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.1479  loss: 1.1479
2022/08/02 10:04:53 - mmengine - INFO - Epoch(train) [20][2500/3757]  lr: 2.9665e-05  eta: 7:31:46  time: 0.7043  data_time: 0.0161  memory: 45143  top1_acc: 0.3750  top5_acc: 0.6250  loss_cls: 1.3617  loss: 1.3617
2022/08/02 10:06:03 - mmengine - INFO - Epoch(train) [20][2600/3757]  lr: 2.9665e-05  eta: 7:30:36  time: 0.7041  data_time: 0.0171  memory: 45143  top1_acc: 0.6250  top5_acc: 1.0000  loss_cls: 1.1402  loss: 1.1402
2022/08/02 10:06:15 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 10:07:13 - mmengine - INFO - Epoch(train) [20][2700/3757]  lr: 2.9665e-05  eta: 7:29:26  time: 0.7072  data_time: 0.0162  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.1194  loss: 1.1194
2022/08/02 10:08:23 - mmengine - INFO - Epoch(train) [20][2800/3757]  lr: 2.9665e-05  eta: 7:28:17  time: 0.7088  data_time: 0.0159  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 1.2263  loss: 1.2263
2022/08/02 10:09:33 - mmengine - INFO - Epoch(train) [20][2900/3757]  lr: 2.9665e-05  eta: 7:27:07  time: 0.6937  data_time: 0.0170  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.1130  loss: 1.1130
2022/08/02 10:10:42 - mmengine - INFO - Epoch(train) [20][3000/3757]  lr: 2.9665e-05  eta: 7:25:57  time: 0.7040  data_time: 0.0178  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.2543  loss: 1.2543
2022/08/02 10:11:52 - mmengine - INFO - Epoch(train) [20][3100/3757]  lr: 2.9665e-05  eta: 7:24:47  time: 0.7024  data_time: 0.0162  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 1.3058  loss: 1.3058
2022/08/02 10:13:02 - mmengine - INFO - Epoch(train) [20][3200/3757]  lr: 2.9665e-05  eta: 7:23:37  time: 0.7025  data_time: 0.0166  memory: 45143  top1_acc: 0.5000  top5_acc: 0.8750  loss_cls: 1.2772  loss: 1.2772
2022/08/02 10:14:12 - mmengine - INFO - Epoch(train) [20][3300/3757]  lr: 2.9665e-05  eta: 7:22:27  time: 0.6995  data_time: 0.0159  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 1.3860  loss: 1.3860
2022/08/02 10:15:21 - mmengine - INFO - Epoch(train) [20][3400/3757]  lr: 2.9665e-05  eta: 7:21:17  time: 0.6958  data_time: 0.0162  memory: 45143  top1_acc: 1.0000  top5_acc: 1.0000  loss_cls: 1.0403  loss: 1.0403
2022/08/02 10:16:31 - mmengine - INFO - Epoch(train) [20][3500/3757]  lr: 2.9665e-05  eta: 7:20:08  time: 0.7034  data_time: 0.0151  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.0657  loss: 1.0657
2022/08/02 10:17:41 - mmengine - INFO - Epoch(train) [20][3600/3757]  lr: 2.9665e-05  eta: 7:18:58  time: 0.7022  data_time: 0.0157  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 0.9106  loss: 0.9106
2022/08/02 10:17:53 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 10:18:52 - mmengine - INFO - Epoch(train) [20][3700/3757]  lr: 2.9665e-05  eta: 7:17:48  time: 0.7209  data_time: 0.0182  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 0.8585  loss: 0.8585
2022/08/02 10:19:31 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 10:19:31 - mmengine - INFO - Epoch(train) [20][3757/3757]  lr: 2.9665e-05  eta: 7:17:20  time: 0.6828  data_time: 0.0162  memory: 45143  top1_acc: 1.0000  top5_acc: 1.0000  loss_cls: 0.9617  loss: 0.9617
2022/08/02 10:20:43 - mmengine - INFO - Epoch(train) [21][100/3757]  lr: 2.5001e-05  eta: 7:15:54  time: 0.7044  data_time: 0.0172  memory: 45143  top1_acc: 0.6250  top5_acc: 1.0000  loss_cls: 1.3688  loss: 1.3688
2022/08/02 10:21:53 - mmengine - INFO - Epoch(train) [21][200/3757]  lr: 2.5001e-05  eta: 7:14:44  time: 0.6929  data_time: 0.0161  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.3422  loss: 1.3422
2022/08/02 10:23:03 - mmengine - INFO - Epoch(train) [21][300/3757]  lr: 2.5001e-05  eta: 7:13:34  time: 0.6962  data_time: 0.0162  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.1311  loss: 1.1311
2022/08/02 10:24:12 - mmengine - INFO - Epoch(train) [21][400/3757]  lr: 2.5001e-05  eta: 7:12:24  time: 0.7009  data_time: 0.0163  memory: 45143  top1_acc: 0.5000  top5_acc: 0.8750  loss_cls: 1.2196  loss: 1.2196
2022/08/02 10:25:22 - mmengine - INFO - Epoch(train) [21][500/3757]  lr: 2.5001e-05  eta: 7:11:14  time: 0.6914  data_time: 0.0165  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 1.1268  loss: 1.1268
2022/08/02 10:26:32 - mmengine - INFO - Epoch(train) [21][600/3757]  lr: 2.5001e-05  eta: 7:10:04  time: 0.6918  data_time: 0.0149  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.0865  loss: 1.0865
2022/08/02 10:27:41 - mmengine - INFO - Epoch(train) [21][700/3757]  lr: 2.5001e-05  eta: 7:08:55  time: 0.6936  data_time: 0.0153  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.1733  loss: 1.1733
2022/08/02 10:28:51 - mmengine - INFO - Epoch(train) [21][800/3757]  lr: 2.5001e-05  eta: 7:07:45  time: 0.6922  data_time: 0.0150  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 0.9718  loss: 0.9718
2022/08/02 10:29:33 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 10:30:00 - mmengine - INFO - Epoch(train) [21][900/3757]  lr: 2.5001e-05  eta: 7:06:35  time: 0.6921  data_time: 0.0163  memory: 45143  top1_acc: 0.7500  top5_acc: 0.7500  loss_cls: 0.8465  loss: 0.8465
2022/08/02 10:31:10 - mmengine - INFO - Epoch(train) [21][1000/3757]  lr: 2.5001e-05  eta: 7:05:25  time: 0.6909  data_time: 0.0148  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 0.9980  loss: 0.9980
2022/08/02 10:32:20 - mmengine - INFO - Epoch(train) [21][1100/3757]  lr: 2.5001e-05  eta: 7:04:15  time: 0.6948  data_time: 0.0162  memory: 45143  top1_acc: 0.5000  top5_acc: 0.8750  loss_cls: 1.2134  loss: 1.2134
2022/08/02 10:33:29 - mmengine - INFO - Epoch(train) [21][1200/3757]  lr: 2.5001e-05  eta: 7:03:05  time: 0.6937  data_time: 0.0154  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.2492  loss: 1.2492
2022/08/02 10:34:39 - mmengine - INFO - Epoch(train) [21][1300/3757]  lr: 2.5001e-05  eta: 7:01:55  time: 0.6949  data_time: 0.0151  memory: 45143  top1_acc: 0.6250  top5_acc: 1.0000  loss_cls: 0.9597  loss: 0.9597
2022/08/02 10:35:49 - mmengine - INFO - Epoch(train) [21][1400/3757]  lr: 2.5001e-05  eta: 7:00:45  time: 0.6936  data_time: 0.0168  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.3588  loss: 1.3588
2022/08/02 10:36:59 - mmengine - INFO - Epoch(train) [21][1500/3757]  lr: 2.5001e-05  eta: 6:59:36  time: 0.6914  data_time: 0.0161  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.3325  loss: 1.3325
2022/08/02 10:38:10 - mmengine - INFO - Epoch(train) [21][1600/3757]  lr: 2.5001e-05  eta: 6:58:26  time: 0.7277  data_time: 0.0161  memory: 45143  top1_acc: 0.6250  top5_acc: 1.0000  loss_cls: 0.9292  loss: 0.9292
2022/08/02 10:39:20 - mmengine - INFO - Epoch(train) [21][1700/3757]  lr: 2.5001e-05  eta: 6:57:17  time: 0.6999  data_time: 0.0161  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.0602  loss: 1.0602
2022/08/02 10:40:30 - mmengine - INFO - Epoch(train) [21][1800/3757]  lr: 2.5001e-05  eta: 6:56:07  time: 0.6914  data_time: 0.0150  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 1.1734  loss: 1.1734
2022/08/02 10:41:12 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 10:41:39 - mmengine - INFO - Epoch(train) [21][1900/3757]  lr: 2.5001e-05  eta: 6:54:57  time: 0.6952  data_time: 0.0167  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.0416  loss: 1.0416
2022/08/02 10:42:49 - mmengine - INFO - Epoch(train) [21][2000/3757]  lr: 2.5001e-05  eta: 6:53:47  time: 0.6946  data_time: 0.0159  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.2132  loss: 1.2132
2022/08/02 10:43:59 - mmengine - INFO - Epoch(train) [21][2100/3757]  lr: 2.5001e-05  eta: 6:52:37  time: 0.6971  data_time: 0.0159  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.4289  loss: 1.4289
2022/08/02 10:45:09 - mmengine - INFO - Epoch(train) [21][2200/3757]  lr: 2.5001e-05  eta: 6:51:28  time: 0.6941  data_time: 0.0144  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 1.0419  loss: 1.0419
2022/08/02 10:46:18 - mmengine - INFO - Epoch(train) [21][2300/3757]  lr: 2.5001e-05  eta: 6:50:18  time: 0.6935  data_time: 0.0162  memory: 45143  top1_acc: 0.5000  top5_acc: 0.8750  loss_cls: 1.3417  loss: 1.3417
2022/08/02 10:47:28 - mmengine - INFO - Epoch(train) [21][2400/3757]  lr: 2.5001e-05  eta: 6:49:08  time: 0.6931  data_time: 0.0150  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 0.9219  loss: 0.9219
2022/08/02 10:48:38 - mmengine - INFO - Epoch(train) [21][2500/3757]  lr: 2.5001e-05  eta: 6:47:58  time: 0.6938  data_time: 0.0172  memory: 45143  top1_acc: 0.6250  top5_acc: 1.0000  loss_cls: 1.2920  loss: 1.2920
2022/08/02 10:49:48 - mmengine - INFO - Epoch(train) [21][2600/3757]  lr: 2.5001e-05  eta: 6:46:48  time: 0.6966  data_time: 0.0163  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.0818  loss: 1.0818
2022/08/02 10:50:57 - mmengine - INFO - Epoch(train) [21][2700/3757]  lr: 2.5001e-05  eta: 6:45:38  time: 0.6930  data_time: 0.0163  memory: 45143  top1_acc: 0.5000  top5_acc: 0.8750  loss_cls: 1.0780  loss: 1.0780
2022/08/02 10:52:07 - mmengine - INFO - Epoch(train) [21][2800/3757]  lr: 2.5001e-05  eta: 6:44:28  time: 0.6946  data_time: 0.0167  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 1.0277  loss: 1.0277
2022/08/02 10:52:49 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 10:53:17 - mmengine - INFO - Epoch(train) [21][2900/3757]  lr: 2.5001e-05  eta: 6:43:19  time: 0.7018  data_time: 0.0170  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.2029  loss: 1.2029
2022/08/02 10:54:27 - mmengine - INFO - Epoch(train) [21][3000/3757]  lr: 2.5001e-05  eta: 6:42:09  time: 0.7036  data_time: 0.0163  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.2103  loss: 1.2103
2022/08/02 10:55:37 - mmengine - INFO - Epoch(train) [21][3100/3757]  lr: 2.5001e-05  eta: 6:40:59  time: 0.6999  data_time: 0.0160  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.2542  loss: 1.2542
2022/08/02 10:56:47 - mmengine - INFO - Epoch(train) [21][3200/3757]  lr: 2.5001e-05  eta: 6:39:50  time: 0.7013  data_time: 0.0163  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 1.1582  loss: 1.1582
2022/08/02 10:57:57 - mmengine - INFO - Epoch(train) [21][3300/3757]  lr: 2.5001e-05  eta: 6:38:40  time: 0.7020  data_time: 0.0167  memory: 45143  top1_acc: 0.5000  top5_acc: 1.0000  loss_cls: 1.1598  loss: 1.1598
2022/08/02 10:59:07 - mmengine - INFO - Epoch(train) [21][3400/3757]  lr: 2.5001e-05  eta: 6:37:30  time: 0.6942  data_time: 0.0168  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.1708  loss: 1.1708
2022/08/02 11:00:16 - mmengine - INFO - Epoch(train) [21][3500/3757]  lr: 2.5001e-05  eta: 6:36:20  time: 0.7018  data_time: 0.0162  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 0.9589  loss: 0.9589
2022/08/02 11:01:26 - mmengine - INFO - Epoch(train) [21][3600/3757]  lr: 2.5001e-05  eta: 6:35:10  time: 0.6978  data_time: 0.0164  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 1.0207  loss: 1.0207
2022/08/02 11:02:35 - mmengine - INFO - Epoch(train) [21][3700/3757]  lr: 2.5001e-05  eta: 6:34:00  time: 0.6964  data_time: 0.0171  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.1078  loss: 1.1078
2022/08/02 11:03:15 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 11:03:15 - mmengine - INFO - Epoch(train) [21][3757/3757]  lr: 2.5001e-05  eta: 6:33:32  time: 0.6901  data_time: 0.0158  memory: 45143  top1_acc: 0.4286  top5_acc: 0.5714  loss_cls: 1.1750  loss: 1.1750
2022/08/02 11:03:15 - mmengine - INFO - Saving checkpoint at 21 epochs
2022/08/02 11:03:52 - mmengine - INFO - Epoch(val) [21][100/310]    eta: 0:00:57  time: 0.2724  data_time: 0.0115  memory: 8742  
2022/08/02 11:04:20 - mmengine - INFO - Epoch(val) [21][200/310]    eta: 0:00:31  time: 0.2822  data_time: 0.0122  memory: 8742  
2022/08/02 11:04:46 - mmengine - INFO - Epoch(val) [21][300/310]    eta: 0:00:02  time: 0.2617  data_time: 0.0093  memory: 8742  
2022/08/02 11:04:50 - mmengine - INFO - Epoch(val) [21][310/310]  acc/top1: 0.7405  acc/top5: 0.9083  acc/mean1: 0.7403
2022/08/02 11:04:50 - mmengine - INFO - The previous best checkpoint /mnt/lustre/daiwenxun/X/mmaction2/work_dirs/swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb/best_acc/top1_epoch_19.pth is removed
2022/08/02 11:04:53 - mmengine - INFO - The best checkpoint with 0.7405 acc/top1 at 22 epoch is saved to best_acc/top1_epoch_22.pth.
2022/08/02 11:06:03 - mmengine - INFO - Epoch(train) [22][100/3757]  lr: 2.0612e-05  eta: 6:32:06  time: 0.6946  data_time: 0.0159  memory: 45143  top1_acc: 0.7500  top5_acc: 0.7500  loss_cls: 1.2224  loss: 1.2224
2022/08/02 11:06:05 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 11:07:13 - mmengine - INFO - Epoch(train) [22][200/3757]  lr: 2.0612e-05  eta: 6:30:56  time: 0.6920  data_time: 0.0156  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 0.7814  loss: 0.7814
2022/08/02 11:08:22 - mmengine - INFO - Epoch(train) [22][300/3757]  lr: 2.0612e-05  eta: 6:29:46  time: 0.6920  data_time: 0.0167  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 1.4039  loss: 1.4039
2022/08/02 11:09:32 - mmengine - INFO - Epoch(train) [22][400/3757]  lr: 2.0612e-05  eta: 6:28:36  time: 0.6911  data_time: 0.0154  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 0.9376  loss: 0.9376
2022/08/02 11:10:42 - mmengine - INFO - Epoch(train) [22][500/3757]  lr: 2.0612e-05  eta: 6:27:26  time: 0.7046  data_time: 0.0171  memory: 45143  top1_acc: 0.3750  top5_acc: 0.7500  loss_cls: 1.1119  loss: 1.1119
2022/08/02 11:11:52 - mmengine - INFO - Epoch(train) [22][600/3757]  lr: 2.0612e-05  eta: 6:26:17  time: 0.6918  data_time: 0.0155  memory: 45143  top1_acc: 0.6250  top5_acc: 1.0000  loss_cls: 0.9691  loss: 0.9691
2022/08/02 11:13:02 - mmengine - INFO - Epoch(train) [22][700/3757]  lr: 2.0612e-05  eta: 6:25:07  time: 0.6975  data_time: 0.0155  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 1.1160  loss: 1.1160
2022/08/02 11:14:11 - mmengine - INFO - Epoch(train) [22][800/3757]  lr: 2.0612e-05  eta: 6:23:57  time: 0.6911  data_time: 0.0146  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.0140  loss: 1.0140
2022/08/02 11:15:21 - mmengine - INFO - Epoch(train) [22][900/3757]  lr: 2.0612e-05  eta: 6:22:47  time: 0.6917  data_time: 0.0162  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.0459  loss: 1.0459
2022/08/02 11:16:30 - mmengine - INFO - Epoch(train) [22][1000/3757]  lr: 2.0612e-05  eta: 6:21:37  time: 0.6941  data_time: 0.0171  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.3318  loss: 1.3318
2022/08/02 11:17:40 - mmengine - INFO - Epoch(train) [22][1100/3757]  lr: 2.0612e-05  eta: 6:20:27  time: 0.6934  data_time: 0.0168  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 1.1939  loss: 1.1939
2022/08/02 11:17:42 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 11:18:50 - mmengine - INFO - Epoch(train) [22][1200/3757]  lr: 2.0612e-05  eta: 6:19:18  time: 0.6954  data_time: 0.0174  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 0.9332  loss: 0.9332
2022/08/02 11:20:00 - mmengine - INFO - Epoch(train) [22][1300/3757]  lr: 2.0612e-05  eta: 6:18:08  time: 0.7024  data_time: 0.0167  memory: 45143  top1_acc: 0.6250  top5_acc: 1.0000  loss_cls: 1.1658  loss: 1.1658
2022/08/02 11:21:09 - mmengine - INFO - Epoch(train) [22][1400/3757]  lr: 2.0612e-05  eta: 6:16:58  time: 0.6936  data_time: 0.0166  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 0.7867  loss: 0.7867
2022/08/02 11:22:20 - mmengine - INFO - Epoch(train) [22][1500/3757]  lr: 2.0612e-05  eta: 6:15:48  time: 0.7048  data_time: 0.0161  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 0.8442  loss: 0.8442
2022/08/02 11:23:30 - mmengine - INFO - Epoch(train) [22][1600/3757]  lr: 2.0612e-05  eta: 6:14:39  time: 0.7082  data_time: 0.0169  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.1025  loss: 1.1025
2022/08/02 11:24:39 - mmengine - INFO - Epoch(train) [22][1700/3757]  lr: 2.0612e-05  eta: 6:13:29  time: 0.6936  data_time: 0.0164  memory: 45143  top1_acc: 0.6250  top5_acc: 0.6250  loss_cls: 1.2140  loss: 1.2140
2022/08/02 11:25:49 - mmengine - INFO - Epoch(train) [22][1800/3757]  lr: 2.0612e-05  eta: 6:12:19  time: 0.6947  data_time: 0.0161  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.0390  loss: 1.0390
2022/08/02 11:26:59 - mmengine - INFO - Epoch(train) [22][1900/3757]  lr: 2.0612e-05  eta: 6:11:09  time: 0.7054  data_time: 0.0178  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.2391  loss: 1.2391
2022/08/02 11:28:09 - mmengine - INFO - Epoch(train) [22][2000/3757]  lr: 2.0612e-05  eta: 6:10:00  time: 0.7129  data_time: 0.0154  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 0.9487  loss: 0.9487
2022/08/02 11:29:20 - mmengine - INFO - Epoch(train) [22][2100/3757]  lr: 2.0612e-05  eta: 6:08:50  time: 0.7105  data_time: 0.0165  memory: 45143  top1_acc: 1.0000  top5_acc: 1.0000  loss_cls: 1.0335  loss: 1.0335
2022/08/02 11:29:22 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 11:30:30 - mmengine - INFO - Epoch(train) [22][2200/3757]  lr: 2.0612e-05  eta: 6:07:40  time: 0.7086  data_time: 0.0161  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 0.8660  loss: 0.8660
2022/08/02 11:31:40 - mmengine - INFO - Epoch(train) [22][2300/3757]  lr: 2.0612e-05  eta: 6:06:31  time: 0.6968  data_time: 0.0168  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.5065  loss: 1.5065
2022/08/02 11:32:49 - mmengine - INFO - Epoch(train) [22][2400/3757]  lr: 2.0612e-05  eta: 6:05:21  time: 0.6947  data_time: 0.0156  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 1.1155  loss: 1.1155
2022/08/02 11:33:59 - mmengine - INFO - Epoch(train) [22][2500/3757]  lr: 2.0612e-05  eta: 6:04:11  time: 0.6939  data_time: 0.0165  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.1549  loss: 1.1549
2022/08/02 11:35:09 - mmengine - INFO - Epoch(train) [22][2600/3757]  lr: 2.0612e-05  eta: 6:03:01  time: 0.6964  data_time: 0.0158  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.1543  loss: 1.1543
2022/08/02 11:36:19 - mmengine - INFO - Epoch(train) [22][2700/3757]  lr: 2.0612e-05  eta: 6:01:52  time: 0.7030  data_time: 0.0166  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 1.2838  loss: 1.2838
2022/08/02 11:37:29 - mmengine - INFO - Epoch(train) [22][2800/3757]  lr: 2.0612e-05  eta: 6:00:42  time: 0.6970  data_time: 0.0160  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.0549  loss: 1.0549
2022/08/02 11:38:38 - mmengine - INFO - Epoch(train) [22][2900/3757]  lr: 2.0612e-05  eta: 5:59:32  time: 0.6927  data_time: 0.0157  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 0.9616  loss: 0.9616
2022/08/02 11:39:48 - mmengine - INFO - Epoch(train) [22][3000/3757]  lr: 2.0612e-05  eta: 5:58:22  time: 0.6973  data_time: 0.0158  memory: 45143  top1_acc: 1.0000  top5_acc: 1.0000  loss_cls: 1.1862  loss: 1.1862
2022/08/02 11:40:57 - mmengine - INFO - Epoch(train) [22][3100/3757]  lr: 2.0612e-05  eta: 5:57:12  time: 0.6912  data_time: 0.0147  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 0.9416  loss: 0.9416
2022/08/02 11:40:59 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 11:42:07 - mmengine - INFO - Epoch(train) [22][3200/3757]  lr: 2.0612e-05  eta: 5:56:02  time: 0.7025  data_time: 0.0148  memory: 45143  top1_acc: 1.0000  top5_acc: 1.0000  loss_cls: 0.8826  loss: 0.8826
2022/08/02 11:43:17 - mmengine - INFO - Epoch(train) [22][3300/3757]  lr: 2.0612e-05  eta: 5:54:52  time: 0.6932  data_time: 0.0165  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.2014  loss: 1.2014
2022/08/02 11:44:26 - mmengine - INFO - Epoch(train) [22][3400/3757]  lr: 2.0612e-05  eta: 5:53:43  time: 0.6930  data_time: 0.0153  memory: 45143  top1_acc: 0.6250  top5_acc: 1.0000  loss_cls: 1.1326  loss: 1.1326
2022/08/02 11:45:37 - mmengine - INFO - Epoch(train) [22][3500/3757]  lr: 2.0612e-05  eta: 5:52:33  time: 0.6918  data_time: 0.0164  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 1.0252  loss: 1.0252
2022/08/02 11:46:47 - mmengine - INFO - Epoch(train) [22][3600/3757]  lr: 2.0612e-05  eta: 5:51:23  time: 0.6940  data_time: 0.0161  memory: 45143  top1_acc: 0.5000  top5_acc: 0.6250  loss_cls: 1.2588  loss: 1.2588
2022/08/02 11:47:57 - mmengine - INFO - Epoch(train) [22][3700/3757]  lr: 2.0612e-05  eta: 5:50:14  time: 0.6932  data_time: 0.0159  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 0.9892  loss: 0.9892
2022/08/02 11:48:36 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 11:48:36 - mmengine - INFO - Epoch(train) [22][3757/3757]  lr: 2.0612e-05  eta: 5:49:46  time: 0.6842  data_time: 0.0158  memory: 45143  top1_acc: 0.8571  top5_acc: 1.0000  loss_cls: 0.8471  loss: 0.8471
2022/08/02 11:49:48 - mmengine - INFO - Epoch(train) [23][100/3757]  lr: 1.6544e-05  eta: 5:48:21  time: 0.6929  data_time: 0.0160  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 0.9338  loss: 0.9338
2022/08/02 11:50:58 - mmengine - INFO - Epoch(train) [23][200/3757]  lr: 1.6544e-05  eta: 5:47:11  time: 0.6954  data_time: 0.0154  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.0066  loss: 1.0066
2022/08/02 11:52:08 - mmengine - INFO - Epoch(train) [23][300/3757]  lr: 1.6544e-05  eta: 5:46:01  time: 0.6950  data_time: 0.0163  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.1545  loss: 1.1545
2022/08/02 11:52:40 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 11:53:18 - mmengine - INFO - Epoch(train) [23][400/3757]  lr: 1.6544e-05  eta: 5:44:51  time: 0.6944  data_time: 0.0149  memory: 45143  top1_acc: 0.6250  top5_acc: 1.0000  loss_cls: 1.1197  loss: 1.1197
2022/08/02 11:54:27 - mmengine - INFO - Epoch(train) [23][500/3757]  lr: 1.6544e-05  eta: 5:43:41  time: 0.6917  data_time: 0.0158  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 0.8656  loss: 0.8656
2022/08/02 11:55:37 - mmengine - INFO - Epoch(train) [23][600/3757]  lr: 1.6544e-05  eta: 5:42:32  time: 0.6932  data_time: 0.0157  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 1.0007  loss: 1.0007
2022/08/02 11:56:47 - mmengine - INFO - Epoch(train) [23][700/3757]  lr: 1.6544e-05  eta: 5:41:22  time: 0.6913  data_time: 0.0159  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 0.9495  loss: 0.9495
2022/08/02 11:57:57 - mmengine - INFO - Epoch(train) [23][800/3757]  lr: 1.6544e-05  eta: 5:40:12  time: 0.6915  data_time: 0.0155  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.1337  loss: 1.1337
2022/08/02 11:59:06 - mmengine - INFO - Epoch(train) [23][900/3757]  lr: 1.6544e-05  eta: 5:39:02  time: 0.7006  data_time: 0.0161  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 1.0360  loss: 1.0360
2022/08/02 12:00:18 - mmengine - INFO - Epoch(train) [23][1000/3757]  lr: 1.6544e-05  eta: 5:37:53  time: 0.6912  data_time: 0.0145  memory: 45143  top1_acc: 0.3750  top5_acc: 1.0000  loss_cls: 1.0215  loss: 1.0215
2022/08/02 12:01:28 - mmengine - INFO - Epoch(train) [23][1100/3757]  lr: 1.6544e-05  eta: 5:36:43  time: 0.7033  data_time: 0.0162  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 1.0067  loss: 1.0067
2022/08/02 12:02:38 - mmengine - INFO - Epoch(train) [23][1200/3757]  lr: 1.6544e-05  eta: 5:35:34  time: 0.6916  data_time: 0.0154  memory: 45143  top1_acc: 1.0000  top5_acc: 1.0000  loss_cls: 0.9316  loss: 0.9316
2022/08/02 12:03:48 - mmengine - INFO - Epoch(train) [23][1300/3757]  lr: 1.6544e-05  eta: 5:34:24  time: 0.6956  data_time: 0.0154  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.0407  loss: 1.0407
2022/08/02 12:04:20 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 12:04:58 - mmengine - INFO - Epoch(train) [23][1400/3757]  lr: 1.6544e-05  eta: 5:33:14  time: 0.6989  data_time: 0.0160  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.3681  loss: 1.3681
2022/08/02 12:06:08 - mmengine - INFO - Epoch(train) [23][1500/3757]  lr: 1.6544e-05  eta: 5:32:05  time: 0.6924  data_time: 0.0155  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.2224  loss: 1.2224
2022/08/02 12:07:18 - mmengine - INFO - Epoch(train) [23][1600/3757]  lr: 1.6544e-05  eta: 5:30:55  time: 0.6942  data_time: 0.0156  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.0628  loss: 1.0628
2022/08/02 12:08:28 - mmengine - INFO - Epoch(train) [23][1700/3757]  lr: 1.6544e-05  eta: 5:29:45  time: 0.6916  data_time: 0.0157  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 0.8952  loss: 0.8952
2022/08/02 12:09:38 - mmengine - INFO - Epoch(train) [23][1800/3757]  lr: 1.6544e-05  eta: 5:28:35  time: 0.6931  data_time: 0.0158  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.1173  loss: 1.1173
2022/08/02 12:10:48 - mmengine - INFO - Epoch(train) [23][1900/3757]  lr: 1.6544e-05  eta: 5:27:26  time: 0.6929  data_time: 0.0156  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 0.9349  loss: 0.9349
2022/08/02 12:11:58 - mmengine - INFO - Epoch(train) [23][2000/3757]  lr: 1.6544e-05  eta: 5:26:16  time: 0.7007  data_time: 0.0159  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 1.0435  loss: 1.0435
2022/08/02 12:13:07 - mmengine - INFO - Epoch(train) [23][2100/3757]  lr: 1.6544e-05  eta: 5:25:06  time: 0.6911  data_time: 0.0153  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.0867  loss: 1.0867
2022/08/02 12:14:17 - mmengine - INFO - Epoch(train) [23][2200/3757]  lr: 1.6544e-05  eta: 5:23:56  time: 0.7053  data_time: 0.0161  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 0.9150  loss: 0.9150
2022/08/02 12:15:27 - mmengine - INFO - Epoch(train) [23][2300/3757]  lr: 1.6544e-05  eta: 5:22:47  time: 0.6920  data_time: 0.0149  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 0.6512  loss: 0.6512
2022/08/02 12:15:59 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 12:16:37 - mmengine - INFO - Epoch(train) [23][2400/3757]  lr: 1.6544e-05  eta: 5:21:37  time: 0.6947  data_time: 0.0165  memory: 45143  top1_acc: 0.7500  top5_acc: 0.7500  loss_cls: 1.3193  loss: 1.3193
2022/08/02 12:17:47 - mmengine - INFO - Epoch(train) [23][2500/3757]  lr: 1.6544e-05  eta: 5:20:27  time: 0.6941  data_time: 0.0163  memory: 45143  top1_acc: 0.6250  top5_acc: 1.0000  loss_cls: 0.8694  loss: 0.8694
2022/08/02 12:18:56 - mmengine - INFO - Epoch(train) [23][2600/3757]  lr: 1.6544e-05  eta: 5:19:17  time: 0.6933  data_time: 0.0161  memory: 45143  top1_acc: 0.6250  top5_acc: 1.0000  loss_cls: 1.0415  loss: 1.0415
2022/08/02 12:20:06 - mmengine - INFO - Epoch(train) [23][2700/3757]  lr: 1.6544e-05  eta: 5:18:07  time: 0.6925  data_time: 0.0157  memory: 45143  top1_acc: 0.7500  top5_acc: 0.7500  loss_cls: 1.0700  loss: 1.0700
2022/08/02 12:21:16 - mmengine - INFO - Epoch(train) [23][2800/3757]  lr: 1.6544e-05  eta: 5:16:58  time: 0.6981  data_time: 0.0168  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.1977  loss: 1.1977
2022/08/02 12:22:26 - mmengine - INFO - Epoch(train) [23][2900/3757]  lr: 1.6544e-05  eta: 5:15:48  time: 0.6960  data_time: 0.0177  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 0.9714  loss: 0.9714
2022/08/02 12:23:35 - mmengine - INFO - Epoch(train) [23][3000/3757]  lr: 1.6544e-05  eta: 5:14:38  time: 0.6927  data_time: 0.0160  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 0.8296  loss: 0.8296
2022/08/02 12:24:47 - mmengine - INFO - Epoch(train) [23][3100/3757]  lr: 1.6544e-05  eta: 5:13:29  time: 0.7168  data_time: 0.0175  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.0288  loss: 1.0288
2022/08/02 12:25:57 - mmengine - INFO - Epoch(train) [23][3200/3757]  lr: 1.6544e-05  eta: 5:12:19  time: 0.7040  data_time: 0.0169  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.0989  loss: 1.0989
2022/08/02 12:27:07 - mmengine - INFO - Epoch(train) [23][3300/3757]  lr: 1.6544e-05  eta: 5:11:09  time: 0.7043  data_time: 0.0161  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.0894  loss: 1.0894
2022/08/02 12:27:39 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 12:28:17 - mmengine - INFO - Epoch(train) [23][3400/3757]  lr: 1.6544e-05  eta: 5:10:00  time: 0.7060  data_time: 0.0168  memory: 45143  top1_acc: 1.0000  top5_acc: 1.0000  loss_cls: 1.0137  loss: 1.0137
2022/08/02 12:29:26 - mmengine - INFO - Epoch(train) [23][3500/3757]  lr: 1.6544e-05  eta: 5:08:50  time: 0.6929  data_time: 0.0166  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.0026  loss: 1.0026
2022/08/02 12:30:37 - mmengine - INFO - Epoch(train) [23][3600/3757]  lr: 1.6544e-05  eta: 5:07:40  time: 0.6939  data_time: 0.0163  memory: 45143  top1_acc: 0.6250  top5_acc: 1.0000  loss_cls: 0.9499  loss: 0.9499
2022/08/02 12:31:47 - mmengine - INFO - Epoch(train) [23][3700/3757]  lr: 1.6544e-05  eta: 5:06:30  time: 0.6986  data_time: 0.0154  memory: 45143  top1_acc: 0.6250  top5_acc: 1.0000  loss_cls: 0.9918  loss: 0.9918
2022/08/02 12:32:27 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 12:32:27 - mmengine - INFO - Epoch(train) [23][3757/3757]  lr: 1.6544e-05  eta: 5:06:02  time: 0.7102  data_time: 0.0175  memory: 45143  top1_acc: 0.5714  top5_acc: 0.7143  loss_cls: 1.1060  loss: 1.1060
2022/08/02 12:33:39 - mmengine - INFO - Epoch(train) [24][100/3757]  lr: 1.2843e-05  eta: 5:04:38  time: 0.6915  data_time: 0.0148  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 1.3083  loss: 1.3083
2022/08/02 12:34:49 - mmengine - INFO - Epoch(train) [24][200/3757]  lr: 1.2843e-05  eta: 5:03:28  time: 0.6952  data_time: 0.0157  memory: 45143  top1_acc: 0.5000  top5_acc: 0.8750  loss_cls: 1.0248  loss: 1.0248
2022/08/02 12:35:59 - mmengine - INFO - Epoch(train) [24][300/3757]  lr: 1.2843e-05  eta: 5:02:18  time: 0.7002  data_time: 0.0163  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 0.9870  loss: 0.9870
2022/08/02 12:37:09 - mmengine - INFO - Epoch(train) [24][400/3757]  lr: 1.2843e-05  eta: 5:01:09  time: 0.6923  data_time: 0.0164  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.2044  loss: 1.2044
2022/08/02 12:38:19 - mmengine - INFO - Epoch(train) [24][500/3757]  lr: 1.2843e-05  eta: 4:59:59  time: 0.6997  data_time: 0.0169  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 0.7280  loss: 0.7280
2022/08/02 12:39:21 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 12:39:29 - mmengine - INFO - Epoch(train) [24][600/3757]  lr: 1.2843e-05  eta: 4:58:49  time: 0.6920  data_time: 0.0157  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 0.9745  loss: 0.9745
2022/08/02 12:40:39 - mmengine - INFO - Epoch(train) [24][700/3757]  lr: 1.2843e-05  eta: 4:57:40  time: 0.6954  data_time: 0.0172  memory: 45143  top1_acc: 1.0000  top5_acc: 1.0000  loss_cls: 0.9586  loss: 0.9586
2022/08/02 12:41:49 - mmengine - INFO - Epoch(train) [24][800/3757]  lr: 1.2843e-05  eta: 4:56:30  time: 0.6941  data_time: 0.0161  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 0.8855  loss: 0.8855
2022/08/02 12:42:59 - mmengine - INFO - Epoch(train) [24][900/3757]  lr: 1.2843e-05  eta: 4:55:20  time: 0.7014  data_time: 0.0162  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 0.9395  loss: 0.9395
2022/08/02 12:44:09 - mmengine - INFO - Epoch(train) [24][1000/3757]  lr: 1.2843e-05  eta: 4:54:11  time: 0.6972  data_time: 0.0156  memory: 45143  top1_acc: 1.0000  top5_acc: 1.0000  loss_cls: 1.0077  loss: 1.0077
2022/08/02 12:45:19 - mmengine - INFO - Epoch(train) [24][1100/3757]  lr: 1.2843e-05  eta: 4:53:01  time: 0.6933  data_time: 0.0164  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 0.8924  loss: 0.8924
2022/08/02 12:46:29 - mmengine - INFO - Epoch(train) [24][1200/3757]  lr: 1.2843e-05  eta: 4:51:51  time: 0.7021  data_time: 0.0165  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.2140  loss: 1.2140
2022/08/02 12:47:39 - mmengine - INFO - Epoch(train) [24][1300/3757]  lr: 1.2843e-05  eta: 4:50:42  time: 0.6926  data_time: 0.0161  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.1862  loss: 1.1862
2022/08/02 12:48:49 - mmengine - INFO - Epoch(train) [24][1400/3757]  lr: 1.2843e-05  eta: 4:49:32  time: 0.7061  data_time: 0.0170  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.1324  loss: 1.1324
2022/08/02 12:49:59 - mmengine - INFO - Epoch(train) [24][1500/3757]  lr: 1.2843e-05  eta: 4:48:22  time: 0.7038  data_time: 0.0164  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 0.9715  loss: 0.9715
2022/08/02 12:51:01 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 12:51:09 - mmengine - INFO - Epoch(train) [24][1600/3757]  lr: 1.2843e-05  eta: 4:47:12  time: 0.6991  data_time: 0.0169  memory: 45143  top1_acc: 1.0000  top5_acc: 1.0000  loss_cls: 0.7552  loss: 0.7552
2022/08/02 12:52:19 - mmengine - INFO - Epoch(train) [24][1700/3757]  lr: 1.2843e-05  eta: 4:46:03  time: 0.6944  data_time: 0.0165  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.0091  loss: 1.0091
2022/08/02 12:53:29 - mmengine - INFO - Epoch(train) [24][1800/3757]  lr: 1.2843e-05  eta: 4:44:53  time: 0.7040  data_time: 0.0173  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 1.2532  loss: 1.2532
2022/08/02 12:54:39 - mmengine - INFO - Epoch(train) [24][1900/3757]  lr: 1.2843e-05  eta: 4:43:43  time: 0.6971  data_time: 0.0175  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 0.8131  loss: 0.8131
2022/08/02 12:55:49 - mmengine - INFO - Epoch(train) [24][2000/3757]  lr: 1.2843e-05  eta: 4:42:33  time: 0.7041  data_time: 0.0169  memory: 45143  top1_acc: 0.6250  top5_acc: 1.0000  loss_cls: 1.0869  loss: 1.0869
2022/08/02 12:56:59 - mmengine - INFO - Epoch(train) [24][2100/3757]  lr: 1.2843e-05  eta: 4:41:24  time: 0.6947  data_time: 0.0158  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 0.9027  loss: 0.9027
2022/08/02 12:58:08 - mmengine - INFO - Epoch(train) [24][2200/3757]  lr: 1.2843e-05  eta: 4:40:14  time: 0.6990  data_time: 0.0170  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 0.9308  loss: 0.9308
2022/08/02 12:59:19 - mmengine - INFO - Epoch(train) [24][2300/3757]  lr: 1.2843e-05  eta: 4:39:04  time: 0.7015  data_time: 0.0177  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 1.1878  loss: 1.1878
2022/08/02 13:00:29 - mmengine - INFO - Epoch(train) [24][2400/3757]  lr: 1.2843e-05  eta: 4:37:54  time: 0.6965  data_time: 0.0159  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.1326  loss: 1.1326
2022/08/02 13:01:38 - mmengine - INFO - Epoch(train) [24][2500/3757]  lr: 1.2843e-05  eta: 4:36:45  time: 0.6920  data_time: 0.0176  memory: 45143  top1_acc: 0.3750  top5_acc: 0.5000  loss_cls: 0.9669  loss: 0.9669
2022/08/02 13:02:40 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 13:02:48 - mmengine - INFO - Epoch(train) [24][2600/3757]  lr: 1.2843e-05  eta: 4:35:35  time: 0.6952  data_time: 0.0189  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 1.1602  loss: 1.1602
2022/08/02 13:03:58 - mmengine - INFO - Epoch(train) [24][2700/3757]  lr: 1.2843e-05  eta: 4:34:25  time: 0.6942  data_time: 0.0158  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.0506  loss: 1.0506
2022/08/02 13:05:08 - mmengine - INFO - Epoch(train) [24][2800/3757]  lr: 1.2843e-05  eta: 4:33:15  time: 0.7030  data_time: 0.0168  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 0.9950  loss: 0.9950
2022/08/02 13:06:18 - mmengine - INFO - Epoch(train) [24][2900/3757]  lr: 1.2843e-05  eta: 4:32:06  time: 0.6984  data_time: 0.0169  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 1.1834  loss: 1.1834
2022/08/02 13:07:27 - mmengine - INFO - Epoch(train) [24][3000/3757]  lr: 1.2843e-05  eta: 4:30:56  time: 0.6938  data_time: 0.0159  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 0.8210  loss: 0.8210
2022/08/02 13:08:37 - mmengine - INFO - Epoch(train) [24][3100/3757]  lr: 1.2843e-05  eta: 4:29:46  time: 0.7109  data_time: 0.0175  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.0897  loss: 1.0897
2022/08/02 13:09:47 - mmengine - INFO - Epoch(train) [24][3200/3757]  lr: 1.2843e-05  eta: 4:28:36  time: 0.6990  data_time: 0.0156  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 0.9005  loss: 0.9005
2022/08/02 13:10:57 - mmengine - INFO - Epoch(train) [24][3300/3757]  lr: 1.2843e-05  eta: 4:27:27  time: 0.6950  data_time: 0.0163  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 0.9430  loss: 0.9430
2022/08/02 13:12:07 - mmengine - INFO - Epoch(train) [24][3400/3757]  lr: 1.2843e-05  eta: 4:26:17  time: 0.6933  data_time: 0.0147  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 0.7459  loss: 0.7459
2022/08/02 13:13:17 - mmengine - INFO - Epoch(train) [24][3500/3757]  lr: 1.2843e-05  eta: 4:25:07  time: 0.6968  data_time: 0.0143  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.1709  loss: 1.1709
2022/08/02 13:14:19 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 13:14:27 - mmengine - INFO - Epoch(train) [24][3600/3757]  lr: 1.2843e-05  eta: 4:23:57  time: 0.6992  data_time: 0.0160  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.0322  loss: 1.0322
2022/08/02 13:15:37 - mmengine - INFO - Epoch(train) [24][3700/3757]  lr: 1.2843e-05  eta: 4:22:48  time: 0.6922  data_time: 0.0159  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 0.8608  loss: 0.8608
2022/08/02 13:16:17 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 13:16:17 - mmengine - INFO - Epoch(train) [24][3757/3757]  lr: 1.2843e-05  eta: 4:22:20  time: 0.6856  data_time: 0.0153  memory: 45143  top1_acc: 0.5714  top5_acc: 1.0000  loss_cls: 1.3623  loss: 1.3623
2022/08/02 13:16:17 - mmengine - INFO - Saving checkpoint at 24 epochs
2022/08/02 13:16:53 - mmengine - INFO - Epoch(val) [24][100/310]    eta: 0:00:56  time: 0.2699  data_time: 0.0112  memory: 8742  
2022/08/02 13:17:21 - mmengine - INFO - Epoch(val) [24][200/310]    eta: 0:00:29  time: 0.2705  data_time: 0.0107  memory: 8742  
2022/08/02 13:17:48 - mmengine - INFO - Epoch(val) [24][300/310]    eta: 0:00:02  time: 0.2608  data_time: 0.0088  memory: 8742  
2022/08/02 13:17:51 - mmengine - INFO - Epoch(val) [24][310/310]  acc/top1: 0.7490  acc/top5: 0.9138  acc/mean1: 0.7488
2022/08/02 13:17:51 - mmengine - INFO - The previous best checkpoint /mnt/lustre/daiwenxun/X/mmaction2/work_dirs/swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb/best_acc/top1_epoch_22.pth is removed
2022/08/02 13:17:53 - mmengine - INFO - The best checkpoint with 0.7490 acc/top1 at 25 epoch is saved to best_acc/top1_epoch_25.pth.
2022/08/02 13:19:04 - mmengine - INFO - Epoch(train) [25][100/3757]  lr: 9.5496e-06  eta: 4:20:56  time: 0.6929  data_time: 0.0157  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 1.0825  loss: 1.0825
2022/08/02 13:20:14 - mmengine - INFO - Epoch(train) [25][200/3757]  lr: 9.5496e-06  eta: 4:19:46  time: 0.6991  data_time: 0.0161  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.1220  loss: 1.1220
2022/08/02 13:21:24 - mmengine - INFO - Epoch(train) [25][300/3757]  lr: 9.5496e-06  eta: 4:18:36  time: 0.6971  data_time: 0.0161  memory: 45143  top1_acc: 0.7500  top5_acc: 0.7500  loss_cls: 1.1092  loss: 1.1092
2022/08/02 13:22:34 - mmengine - INFO - Epoch(train) [25][400/3757]  lr: 9.5496e-06  eta: 4:17:26  time: 0.6951  data_time: 0.0166  memory: 45143  top1_acc: 0.5000  top5_acc: 1.0000  loss_cls: 0.8400  loss: 0.8400
2022/08/02 13:23:43 - mmengine - INFO - Epoch(train) [25][500/3757]  lr: 9.5496e-06  eta: 4:16:16  time: 0.6907  data_time: 0.0146  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 0.9875  loss: 0.9875
2022/08/02 13:24:53 - mmengine - INFO - Epoch(train) [25][600/3757]  lr: 9.5496e-06  eta: 4:15:07  time: 0.6953  data_time: 0.0155  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.0382  loss: 1.0382
2022/08/02 13:26:03 - mmengine - INFO - Epoch(train) [25][700/3757]  lr: 9.5496e-06  eta: 4:13:57  time: 0.6960  data_time: 0.0171  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.1104  loss: 1.1104
2022/08/02 13:27:13 - mmengine - INFO - Epoch(train) [25][800/3757]  lr: 9.5496e-06  eta: 4:12:47  time: 0.6954  data_time: 0.0155  memory: 45143  top1_acc: 0.5000  top5_acc: 0.6250  loss_cls: 0.9709  loss: 0.9709
2022/08/02 13:27:35 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 13:28:22 - mmengine - INFO - Epoch(train) [25][900/3757]  lr: 9.5496e-06  eta: 4:11:37  time: 0.7006  data_time: 0.0159  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.1061  loss: 1.1061
2022/08/02 13:29:32 - mmengine - INFO - Epoch(train) [25][1000/3757]  lr: 9.5496e-06  eta: 4:10:28  time: 0.7015  data_time: 0.0168  memory: 45143  top1_acc: 0.5000  top5_acc: 0.8750  loss_cls: 0.9724  loss: 0.9724
2022/08/02 13:30:42 - mmengine - INFO - Epoch(train) [25][1100/3757]  lr: 9.5496e-06  eta: 4:09:18  time: 0.7004  data_time: 0.0166  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 0.8580  loss: 0.8580
2022/08/02 13:31:52 - mmengine - INFO - Epoch(train) [25][1200/3757]  lr: 9.5496e-06  eta: 4:08:08  time: 0.7082  data_time: 0.0160  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 0.9653  loss: 0.9653
2022/08/02 13:33:02 - mmengine - INFO - Epoch(train) [25][1300/3757]  lr: 9.5496e-06  eta: 4:06:58  time: 0.7026  data_time: 0.0160  memory: 45143  top1_acc: 0.7500  top5_acc: 0.7500  loss_cls: 1.1875  loss: 1.1875
2022/08/02 13:34:12 - mmengine - INFO - Epoch(train) [25][1400/3757]  lr: 9.5496e-06  eta: 4:05:49  time: 0.7161  data_time: 0.0168  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 0.9044  loss: 0.9044
2022/08/02 13:35:22 - mmengine - INFO - Epoch(train) [25][1500/3757]  lr: 9.5496e-06  eta: 4:04:39  time: 0.6994  data_time: 0.0161  memory: 45143  top1_acc: 0.6250  top5_acc: 1.0000  loss_cls: 1.0991  loss: 1.0991
2022/08/02 13:36:31 - mmengine - INFO - Epoch(train) [25][1600/3757]  lr: 9.5496e-06  eta: 4:03:29  time: 0.7009  data_time: 0.0166  memory: 45143  top1_acc: 1.0000  top5_acc: 1.0000  loss_cls: 0.9908  loss: 0.9908
2022/08/02 13:37:41 - mmengine - INFO - Epoch(train) [25][1700/3757]  lr: 9.5496e-06  eta: 4:02:19  time: 0.7065  data_time: 0.0161  memory: 45143  top1_acc: 1.0000  top5_acc: 1.0000  loss_cls: 1.0758  loss: 1.0758
2022/08/02 13:38:51 - mmengine - INFO - Epoch(train) [25][1800/3757]  lr: 9.5496e-06  eta: 4:01:10  time: 0.6949  data_time: 0.0167  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 0.8821  loss: 0.8821
2022/08/02 13:39:13 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 13:40:01 - mmengine - INFO - Epoch(train) [25][1900/3757]  lr: 9.5496e-06  eta: 4:00:00  time: 0.6950  data_time: 0.0156  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.0383  loss: 1.0383
2022/08/02 13:41:11 - mmengine - INFO - Epoch(train) [25][2000/3757]  lr: 9.5496e-06  eta: 3:58:50  time: 0.7018  data_time: 0.0172  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.2202  loss: 1.2202
2022/08/02 13:42:21 - mmengine - INFO - Epoch(train) [25][2100/3757]  lr: 9.5496e-06  eta: 3:57:40  time: 0.7026  data_time: 0.0163  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 0.9615  loss: 0.9615
2022/08/02 13:43:31 - mmengine - INFO - Epoch(train) [25][2200/3757]  lr: 9.5496e-06  eta: 3:56:31  time: 0.6946  data_time: 0.0154  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.0250  loss: 1.0250
2022/08/02 13:44:42 - mmengine - INFO - Epoch(train) [25][2300/3757]  lr: 9.5496e-06  eta: 3:55:21  time: 0.7060  data_time: 0.0154  memory: 45143  top1_acc: 1.0000  top5_acc: 1.0000  loss_cls: 0.8305  loss: 0.8305
2022/08/02 13:45:52 - mmengine - INFO - Epoch(train) [25][2400/3757]  lr: 9.5496e-06  eta: 3:54:12  time: 0.6937  data_time: 0.0163  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.0429  loss: 1.0429
2022/08/02 13:47:02 - mmengine - INFO - Epoch(train) [25][2500/3757]  lr: 9.5496e-06  eta: 3:53:02  time: 0.7376  data_time: 0.0173  memory: 45143  top1_acc: 0.7500  top5_acc: 0.7500  loss_cls: 1.0684  loss: 1.0684
2022/08/02 13:48:12 - mmengine - INFO - Epoch(train) [25][2600/3757]  lr: 9.5496e-06  eta: 3:51:52  time: 0.7118  data_time: 0.0176  memory: 45143  top1_acc: 0.6250  top5_acc: 1.0000  loss_cls: 1.0033  loss: 1.0033
2022/08/02 13:49:22 - mmengine - INFO - Epoch(train) [25][2700/3757]  lr: 9.5496e-06  eta: 3:50:42  time: 0.6964  data_time: 0.0172  memory: 45143  top1_acc: 0.5000  top5_acc: 0.8750  loss_cls: 0.8889  loss: 0.8889
2022/08/02 13:50:32 - mmengine - INFO - Epoch(train) [25][2800/3757]  lr: 9.5496e-06  eta: 3:49:33  time: 0.6961  data_time: 0.0168  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 1.1270  loss: 1.1270
2022/08/02 13:50:54 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 13:51:41 - mmengine - INFO - Epoch(train) [25][2900/3757]  lr: 9.5496e-06  eta: 3:48:23  time: 0.6961  data_time: 0.0154  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.0902  loss: 1.0902
2022/08/02 13:52:51 - mmengine - INFO - Epoch(train) [25][3000/3757]  lr: 9.5496e-06  eta: 3:47:13  time: 0.6914  data_time: 0.0154  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 0.8647  loss: 0.8647
2022/08/02 13:54:01 - mmengine - INFO - Epoch(train) [25][3100/3757]  lr: 9.5496e-06  eta: 3:46:03  time: 0.7054  data_time: 0.0247  memory: 45143  top1_acc: 1.0000  top5_acc: 1.0000  loss_cls: 0.9320  loss: 0.9320
2022/08/02 13:55:11 - mmengine - INFO - Epoch(train) [25][3200/3757]  lr: 9.5496e-06  eta: 3:44:53  time: 0.6949  data_time: 0.0141  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 0.8135  loss: 0.8135
2022/08/02 13:56:21 - mmengine - INFO - Epoch(train) [25][3300/3757]  lr: 9.5496e-06  eta: 3:43:44  time: 0.7161  data_time: 0.0156  memory: 45143  top1_acc: 0.7500  top5_acc: 0.7500  loss_cls: 0.8053  loss: 0.8053
2022/08/02 13:57:31 - mmengine - INFO - Epoch(train) [25][3400/3757]  lr: 9.5496e-06  eta: 3:42:34  time: 0.6919  data_time: 0.0158  memory: 45143  top1_acc: 0.7500  top5_acc: 0.7500  loss_cls: 1.1719  loss: 1.1719
2022/08/02 13:58:41 - mmengine - INFO - Epoch(train) [25][3500/3757]  lr: 9.5496e-06  eta: 3:41:24  time: 0.6970  data_time: 0.0155  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 0.8432  loss: 0.8432
2022/08/02 13:59:50 - mmengine - INFO - Epoch(train) [25][3600/3757]  lr: 9.5496e-06  eta: 3:40:14  time: 0.6932  data_time: 0.0151  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.2459  loss: 1.2459
2022/08/02 14:01:00 - mmengine - INFO - Epoch(train) [25][3700/3757]  lr: 9.5496e-06  eta: 3:39:05  time: 0.7020  data_time: 0.0164  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 0.9534  loss: 0.9534
2022/08/02 14:01:40 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 14:01:40 - mmengine - INFO - Epoch(train) [25][3757/3757]  lr: 9.5496e-06  eta: 3:38:37  time: 0.6988  data_time: 0.0191  memory: 45143  top1_acc: 0.7143  top5_acc: 1.0000  loss_cls: 0.9824  loss: 0.9824
2022/08/02 14:02:34 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 14:02:52 - mmengine - INFO - Epoch(train) [26][100/3757]  lr: 6.6991e-06  eta: 3:37:13  time: 0.6977  data_time: 0.0166  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 0.8786  loss: 0.8786
2022/08/02 14:04:02 - mmengine - INFO - Epoch(train) [26][200/3757]  lr: 6.6991e-06  eta: 3:36:03  time: 0.7052  data_time: 0.0161  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.2100  loss: 1.2100
2022/08/02 14:05:12 - mmengine - INFO - Epoch(train) [26][300/3757]  lr: 6.6991e-06  eta: 3:34:54  time: 0.6980  data_time: 0.0150  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.0041  loss: 1.0041
2022/08/02 14:06:22 - mmengine - INFO - Epoch(train) [26][400/3757]  lr: 6.6991e-06  eta: 3:33:44  time: 0.6930  data_time: 0.0166  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 0.9333  loss: 0.9333
2022/08/02 14:07:32 - mmengine - INFO - Epoch(train) [26][500/3757]  lr: 6.6991e-06  eta: 3:32:34  time: 0.6908  data_time: 0.0154  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.1286  loss: 1.1286
2022/08/02 14:08:42 - mmengine - INFO - Epoch(train) [26][600/3757]  lr: 6.6991e-06  eta: 3:31:25  time: 0.6946  data_time: 0.0164  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 0.8618  loss: 0.8618
2022/08/02 14:09:51 - mmengine - INFO - Epoch(train) [26][700/3757]  lr: 6.6991e-06  eta: 3:30:15  time: 0.6954  data_time: 0.0153  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 0.9333  loss: 0.9333
2022/08/02 14:11:01 - mmengine - INFO - Epoch(train) [26][800/3757]  lr: 6.6991e-06  eta: 3:29:05  time: 0.6955  data_time: 0.0161  memory: 45143  top1_acc: 1.0000  top5_acc: 1.0000  loss_cls: 0.8993  loss: 0.8993
2022/08/02 14:12:11 - mmengine - INFO - Epoch(train) [26][900/3757]  lr: 6.6991e-06  eta: 3:27:55  time: 0.6913  data_time: 0.0148  memory: 45143  top1_acc: 0.3750  top5_acc: 0.8750  loss_cls: 0.8659  loss: 0.8659
2022/08/02 14:13:21 - mmengine - INFO - Epoch(train) [26][1000/3757]  lr: 6.6991e-06  eta: 3:26:46  time: 0.7113  data_time: 0.0170  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 0.9591  loss: 0.9591
2022/08/02 14:14:13 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 14:14:30 - mmengine - INFO - Epoch(train) [26][1100/3757]  lr: 6.6991e-06  eta: 3:25:36  time: 0.6920  data_time: 0.0158  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 0.9609  loss: 0.9609
2022/08/02 14:15:40 - mmengine - INFO - Epoch(train) [26][1200/3757]  lr: 6.6991e-06  eta: 3:24:26  time: 0.6914  data_time: 0.0150  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 0.9029  loss: 0.9029
2022/08/02 14:16:50 - mmengine - INFO - Epoch(train) [26][1300/3757]  lr: 6.6991e-06  eta: 3:23:16  time: 0.6915  data_time: 0.0159  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.1818  loss: 1.1818
2022/08/02 14:17:59 - mmengine - INFO - Epoch(train) [26][1400/3757]  lr: 6.6991e-06  eta: 3:22:06  time: 0.6961  data_time: 0.0168  memory: 45143  top1_acc: 0.5000  top5_acc: 0.6250  loss_cls: 1.0782  loss: 1.0782
2022/08/02 14:19:09 - mmengine - INFO - Epoch(train) [26][1500/3757]  lr: 6.6991e-06  eta: 3:20:57  time: 0.6921  data_time: 0.0155  memory: 45143  top1_acc: 1.0000  top5_acc: 1.0000  loss_cls: 0.8516  loss: 0.8516
2022/08/02 14:20:19 - mmengine - INFO - Epoch(train) [26][1600/3757]  lr: 6.6991e-06  eta: 3:19:47  time: 0.6945  data_time: 0.0162  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.1891  loss: 1.1891
2022/08/02 14:21:29 - mmengine - INFO - Epoch(train) [26][1700/3757]  lr: 6.6991e-06  eta: 3:18:37  time: 0.6920  data_time: 0.0148  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 0.8286  loss: 0.8286
2022/08/02 14:22:39 - mmengine - INFO - Epoch(train) [26][1800/3757]  lr: 6.6991e-06  eta: 3:17:27  time: 0.7041  data_time: 0.0160  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 0.7466  loss: 0.7466
2022/08/02 14:23:49 - mmengine - INFO - Epoch(train) [26][1900/3757]  lr: 6.6991e-06  eta: 3:16:18  time: 0.6929  data_time: 0.0153  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 0.8662  loss: 0.8662
2022/08/02 14:24:59 - mmengine - INFO - Epoch(train) [26][2000/3757]  lr: 6.6991e-06  eta: 3:15:08  time: 0.7014  data_time: 0.0160  memory: 45143  top1_acc: 1.0000  top5_acc: 1.0000  loss_cls: 1.1200  loss: 1.1200
2022/08/02 14:25:51 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 14:26:08 - mmengine - INFO - Epoch(train) [26][2100/3757]  lr: 6.6991e-06  eta: 3:13:58  time: 0.6929  data_time: 0.0164  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 0.8636  loss: 0.8636
2022/08/02 14:27:18 - mmengine - INFO - Epoch(train) [26][2200/3757]  lr: 6.6991e-06  eta: 3:12:48  time: 0.6960  data_time: 0.0163  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 0.9318  loss: 0.9318
2022/08/02 14:28:27 - mmengine - INFO - Epoch(train) [26][2300/3757]  lr: 6.6991e-06  eta: 3:11:39  time: 0.6952  data_time: 0.0164  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 0.8813  loss: 0.8813
2022/08/02 14:29:37 - mmengine - INFO - Epoch(train) [26][2400/3757]  lr: 6.6991e-06  eta: 3:10:29  time: 0.6929  data_time: 0.0164  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 1.0642  loss: 1.0642
2022/08/02 14:30:47 - mmengine - INFO - Epoch(train) [26][2500/3757]  lr: 6.6991e-06  eta: 3:09:19  time: 0.7018  data_time: 0.0169  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 0.6882  loss: 0.6882
2022/08/02 14:31:57 - mmengine - INFO - Epoch(train) [26][2600/3757]  lr: 6.6991e-06  eta: 3:08:09  time: 0.6974  data_time: 0.0162  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 0.8760  loss: 0.8760
2022/08/02 14:33:07 - mmengine - INFO - Epoch(train) [26][2700/3757]  lr: 6.6991e-06  eta: 3:07:00  time: 0.6939  data_time: 0.0164  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 0.9243  loss: 0.9243
2022/08/02 14:34:16 - mmengine - INFO - Epoch(train) [26][2800/3757]  lr: 6.6991e-06  eta: 3:05:50  time: 0.6934  data_time: 0.0172  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.0046  loss: 1.0046
2022/08/02 14:35:26 - mmengine - INFO - Epoch(train) [26][2900/3757]  lr: 6.6991e-06  eta: 3:04:40  time: 0.6936  data_time: 0.0160  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.0401  loss: 1.0401
2022/08/02 14:36:35 - mmengine - INFO - Epoch(train) [26][3000/3757]  lr: 6.6991e-06  eta: 3:03:30  time: 0.6929  data_time: 0.0161  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 0.9217  loss: 0.9217
2022/08/02 14:37:28 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 14:37:45 - mmengine - INFO - Epoch(train) [26][3100/3757]  lr: 6.6991e-06  eta: 3:02:21  time: 0.6976  data_time: 0.0172  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 0.8620  loss: 0.8620
2022/08/02 14:38:54 - mmengine - INFO - Epoch(train) [26][3200/3757]  lr: 6.6991e-06  eta: 3:01:11  time: 0.6916  data_time: 0.0151  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 0.8603  loss: 0.8603
2022/08/02 14:40:04 - mmengine - INFO - Epoch(train) [26][3300/3757]  lr: 6.6991e-06  eta: 3:00:01  time: 0.6973  data_time: 0.0162  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 0.7295  loss: 0.7295
2022/08/02 14:41:14 - mmengine - INFO - Epoch(train) [26][3400/3757]  lr: 6.6991e-06  eta: 2:58:51  time: 0.6914  data_time: 0.0150  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 0.7169  loss: 0.7169
2022/08/02 14:42:24 - mmengine - INFO - Epoch(train) [26][3500/3757]  lr: 6.6991e-06  eta: 2:57:41  time: 0.6944  data_time: 0.0155  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.0807  loss: 1.0807
2022/08/02 14:43:33 - mmengine - INFO - Epoch(train) [26][3600/3757]  lr: 6.6991e-06  eta: 2:56:32  time: 0.6927  data_time: 0.0146  memory: 45143  top1_acc: 0.3750  top5_acc: 0.7500  loss_cls: 0.9519  loss: 0.9519
2022/08/02 14:44:43 - mmengine - INFO - Epoch(train) [26][3700/3757]  lr: 6.6991e-06  eta: 2:55:22  time: 0.6940  data_time: 0.0162  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 0.6856  loss: 0.6856
2022/08/02 14:45:23 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 14:45:23 - mmengine - INFO - Epoch(train) [26][3757/3757]  lr: 6.6991e-06  eta: 2:54:54  time: 0.6954  data_time: 0.0152  memory: 45143  top1_acc: 0.5714  top5_acc: 1.0000  loss_cls: 0.6994  loss: 0.6994
2022/08/02 14:46:35 - mmengine - INFO - Epoch(train) [27][100/3757]  lr: 4.3229e-06  eta: 2:53:31  time: 0.6906  data_time: 0.0143  memory: 45143  top1_acc: 0.7500  top5_acc: 0.7500  loss_cls: 0.9660  loss: 0.9660
2022/08/02 14:47:44 - mmengine - INFO - Epoch(train) [27][200/3757]  lr: 4.3229e-06  eta: 2:52:21  time: 0.6941  data_time: 0.0153  memory: 45143  top1_acc: 0.5000  top5_acc: 0.8750  loss_cls: 1.0150  loss: 1.0150
2022/08/02 14:48:54 - mmengine - INFO - Epoch(train) [27][300/3757]  lr: 4.3229e-06  eta: 2:51:11  time: 0.6912  data_time: 0.0161  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 0.9425  loss: 0.9425
2022/08/02 14:49:07 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 14:50:04 - mmengine - INFO - Epoch(train) [27][400/3757]  lr: 4.3229e-06  eta: 2:50:02  time: 0.6955  data_time: 0.0157  memory: 45143  top1_acc: 0.7500  top5_acc: 0.7500  loss_cls: 1.0976  loss: 1.0976
2022/08/02 14:51:14 - mmengine - INFO - Epoch(train) [27][500/3757]  lr: 4.3229e-06  eta: 2:48:52  time: 0.6928  data_time: 0.0153  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 1.2082  loss: 1.2082
2022/08/02 14:52:24 - mmengine - INFO - Epoch(train) [27][600/3757]  lr: 4.3229e-06  eta: 2:47:42  time: 0.7066  data_time: 0.0161  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 1.1304  loss: 1.1304
2022/08/02 14:53:34 - mmengine - INFO - Epoch(train) [27][700/3757]  lr: 4.3229e-06  eta: 2:46:32  time: 0.6937  data_time: 0.0159  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.1615  loss: 1.1615
2022/08/02 14:54:43 - mmengine - INFO - Epoch(train) [27][800/3757]  lr: 4.3229e-06  eta: 2:45:23  time: 0.6917  data_time: 0.0160  memory: 45143  top1_acc: 0.7500  top5_acc: 0.7500  loss_cls: 0.8267  loss: 0.8267
2022/08/02 14:55:53 - mmengine - INFO - Epoch(train) [27][900/3757]  lr: 4.3229e-06  eta: 2:44:13  time: 0.6916  data_time: 0.0152  memory: 45143  top1_acc: 1.0000  top5_acc: 1.0000  loss_cls: 0.8541  loss: 0.8541
2022/08/02 14:57:03 - mmengine - INFO - Epoch(train) [27][1000/3757]  lr: 4.3229e-06  eta: 2:43:03  time: 0.6920  data_time: 0.0155  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.2786  loss: 1.2786
2022/08/02 14:58:12 - mmengine - INFO - Epoch(train) [27][1100/3757]  lr: 4.3229e-06  eta: 2:41:53  time: 0.6918  data_time: 0.0148  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.0675  loss: 1.0675
2022/08/02 14:59:22 - mmengine - INFO - Epoch(train) [27][1200/3757]  lr: 4.3229e-06  eta: 2:40:44  time: 0.6982  data_time: 0.0160  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.1098  loss: 1.1098
2022/08/02 15:00:32 - mmengine - INFO - Epoch(train) [27][1300/3757]  lr: 4.3229e-06  eta: 2:39:34  time: 0.6932  data_time: 0.0163  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.0569  loss: 1.0569
2022/08/02 15:00:44 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 15:01:41 - mmengine - INFO - Epoch(train) [27][1400/3757]  lr: 4.3229e-06  eta: 2:38:24  time: 0.6974  data_time: 0.0159  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 0.9811  loss: 0.9811
2022/08/02 15:02:51 - mmengine - INFO - Epoch(train) [27][1500/3757]  lr: 4.3229e-06  eta: 2:37:14  time: 0.6962  data_time: 0.0159  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 0.8262  loss: 0.8262
2022/08/02 15:04:00 - mmengine - INFO - Epoch(train) [27][1600/3757]  lr: 4.3229e-06  eta: 2:36:05  time: 0.6995  data_time: 0.0165  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 0.8533  loss: 0.8533
2022/08/02 15:05:10 - mmengine - INFO - Epoch(train) [27][1700/3757]  lr: 4.3229e-06  eta: 2:34:55  time: 0.6991  data_time: 0.0166  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 0.9321  loss: 0.9321
2022/08/02 15:06:19 - mmengine - INFO - Epoch(train) [27][1800/3757]  lr: 4.3229e-06  eta: 2:33:45  time: 0.7009  data_time: 0.0176  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 0.7639  loss: 0.7639
2022/08/02 15:07:29 - mmengine - INFO - Epoch(train) [27][1900/3757]  lr: 4.3229e-06  eta: 2:32:35  time: 0.6995  data_time: 0.0170  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 0.8308  loss: 0.8308
2022/08/02 15:08:39 - mmengine - INFO - Epoch(train) [27][2000/3757]  lr: 4.3229e-06  eta: 2:31:25  time: 0.6982  data_time: 0.0159  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 0.9983  loss: 0.9983
2022/08/02 15:09:49 - mmengine - INFO - Epoch(train) [27][2100/3757]  lr: 4.3229e-06  eta: 2:30:16  time: 0.7160  data_time: 0.0163  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 0.9608  loss: 0.9608
2022/08/02 15:10:59 - mmengine - INFO - Epoch(train) [27][2200/3757]  lr: 4.3229e-06  eta: 2:29:06  time: 0.6975  data_time: 0.0161  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 0.9210  loss: 0.9210
2022/08/02 15:12:09 - mmengine - INFO - Epoch(train) [27][2300/3757]  lr: 4.3229e-06  eta: 2:27:56  time: 0.7062  data_time: 0.0166  memory: 45143  top1_acc: 0.5000  top5_acc: 1.0000  loss_cls: 0.8624  loss: 0.8624
2022/08/02 15:12:22 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 15:13:19 - mmengine - INFO - Epoch(train) [27][2400/3757]  lr: 4.3229e-06  eta: 2:26:47  time: 0.6909  data_time: 0.0151  memory: 45143  top1_acc: 0.6250  top5_acc: 1.0000  loss_cls: 1.0014  loss: 1.0014
2022/08/02 15:14:28 - mmengine - INFO - Epoch(train) [27][2500/3757]  lr: 4.3229e-06  eta: 2:25:37  time: 0.6971  data_time: 0.0165  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 0.8181  loss: 0.8181
2022/08/02 15:15:38 - mmengine - INFO - Epoch(train) [27][2600/3757]  lr: 4.3229e-06  eta: 2:24:27  time: 0.6914  data_time: 0.0150  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 1.0994  loss: 1.0994
2022/08/02 15:16:48 - mmengine - INFO - Epoch(train) [27][2700/3757]  lr: 4.3229e-06  eta: 2:23:17  time: 0.6946  data_time: 0.0166  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 0.7176  loss: 0.7176
2022/08/02 15:17:58 - mmengine - INFO - Epoch(train) [27][2800/3757]  lr: 4.3229e-06  eta: 2:22:08  time: 0.6923  data_time: 0.0143  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 0.8220  loss: 0.8220
2022/08/02 15:19:07 - mmengine - INFO - Epoch(train) [27][2900/3757]  lr: 4.3229e-06  eta: 2:20:58  time: 0.6960  data_time: 0.0152  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.0122  loss: 1.0122
2022/08/02 15:20:17 - mmengine - INFO - Epoch(train) [27][3000/3757]  lr: 4.3229e-06  eta: 2:19:48  time: 0.6917  data_time: 0.0153  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 0.9583  loss: 0.9583
2022/08/02 15:21:27 - mmengine - INFO - Epoch(train) [27][3100/3757]  lr: 4.3229e-06  eta: 2:18:38  time: 0.6969  data_time: 0.0154  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 0.7360  loss: 0.7360
2022/08/02 15:22:36 - mmengine - INFO - Epoch(train) [27][3200/3757]  lr: 4.3229e-06  eta: 2:17:29  time: 0.6920  data_time: 0.0154  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 0.9535  loss: 0.9535
2022/08/02 15:23:46 - mmengine - INFO - Epoch(train) [27][3300/3757]  lr: 4.3229e-06  eta: 2:16:19  time: 0.7044  data_time: 0.0158  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 0.9970  loss: 0.9970
2022/08/02 15:23:59 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 15:24:56 - mmengine - INFO - Epoch(train) [27][3400/3757]  lr: 4.3229e-06  eta: 2:15:09  time: 0.6921  data_time: 0.0151  memory: 45143  top1_acc: 1.0000  top5_acc: 1.0000  loss_cls: 0.8556  loss: 0.8556
2022/08/02 15:26:05 - mmengine - INFO - Epoch(train) [27][3500/3757]  lr: 4.3229e-06  eta: 2:13:59  time: 0.6935  data_time: 0.0162  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 0.8919  loss: 0.8919
2022/08/02 15:27:15 - mmengine - INFO - Epoch(train) [27][3600/3757]  lr: 4.3229e-06  eta: 2:12:50  time: 0.6927  data_time: 0.0154  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 1.0789  loss: 1.0789
2022/08/02 15:28:25 - mmengine - INFO - Epoch(train) [27][3700/3757]  lr: 4.3229e-06  eta: 2:11:40  time: 0.6953  data_time: 0.0162  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.1296  loss: 1.1296
2022/08/02 15:29:04 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 15:29:04 - mmengine - INFO - Epoch(train) [27][3757/3757]  lr: 4.3229e-06  eta: 2:11:12  time: 0.6875  data_time: 0.0167  memory: 45143  top1_acc: 0.7143  top5_acc: 0.8571  loss_cls: 0.9854  loss: 0.9854
2022/08/02 15:29:05 - mmengine - INFO - Saving checkpoint at 27 epochs
2022/08/02 15:29:37 - mmengine - INFO - Epoch(val) [27][100/310]    eta: 0:00:56  time: 0.2692  data_time: 0.0116  memory: 8742  
2022/08/02 15:30:04 - mmengine - INFO - Epoch(val) [27][200/310]    eta: 0:00:30  time: 0.2795  data_time: 0.0134  memory: 8742  
2022/08/02 15:30:31 - mmengine - INFO - Epoch(val) [27][300/310]    eta: 0:00:02  time: 0.2605  data_time: 0.0090  memory: 8742  
2022/08/02 15:30:35 - mmengine - INFO - Epoch(val) [27][310/310]  acc/top1: 0.7536  acc/top5: 0.9159  acc/mean1: 0.7534
2022/08/02 15:30:35 - mmengine - INFO - The previous best checkpoint /mnt/lustre/daiwenxun/X/mmaction2/work_dirs/swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb/best_acc/top1_epoch_25.pth is removed
2022/08/02 15:30:39 - mmengine - INFO - The best checkpoint with 0.7536 acc/top1 at 28 epoch is saved to best_acc/top1_epoch_28.pth.
2022/08/02 15:31:50 - mmengine - INFO - Epoch(train) [28][100/3757]  lr: 2.4473e-06  eta: 2:09:49  time: 0.6950  data_time: 0.0150  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 0.9914  loss: 0.9914
2022/08/02 15:32:59 - mmengine - INFO - Epoch(train) [28][200/3757]  lr: 2.4473e-06  eta: 2:08:39  time: 0.6900  data_time: 0.0147  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 1.0909  loss: 1.0909
2022/08/02 15:34:09 - mmengine - INFO - Epoch(train) [28][300/3757]  lr: 2.4473e-06  eta: 2:07:30  time: 0.6928  data_time: 0.0163  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 0.8985  loss: 0.8985
2022/08/02 15:35:19 - mmengine - INFO - Epoch(train) [28][400/3757]  lr: 2.4473e-06  eta: 2:06:20  time: 0.6954  data_time: 0.0152  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 0.9457  loss: 0.9457
2022/08/02 15:36:28 - mmengine - INFO - Epoch(train) [28][500/3757]  lr: 2.4473e-06  eta: 2:05:10  time: 0.6896  data_time: 0.0155  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.1114  loss: 1.1114
2022/08/02 15:37:11 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 15:37:38 - mmengine - INFO - Epoch(train) [28][600/3757]  lr: 2.4473e-06  eta: 2:04:00  time: 0.7039  data_time: 0.0155  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.0385  loss: 1.0385
2022/08/02 15:38:47 - mmengine - INFO - Epoch(train) [28][700/3757]  lr: 2.4473e-06  eta: 2:02:51  time: 0.6932  data_time: 0.0158  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 1.1209  loss: 1.1209
2022/08/02 15:39:57 - mmengine - INFO - Epoch(train) [28][800/3757]  lr: 2.4473e-06  eta: 2:01:41  time: 0.7015  data_time: 0.0161  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.0278  loss: 1.0278
2022/08/02 15:41:07 - mmengine - INFO - Epoch(train) [28][900/3757]  lr: 2.4473e-06  eta: 2:00:31  time: 0.6920  data_time: 0.0154  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 0.8142  loss: 0.8142
2022/08/02 15:42:16 - mmengine - INFO - Epoch(train) [28][1000/3757]  lr: 2.4473e-06  eta: 1:59:21  time: 0.6976  data_time: 0.0163  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 0.7309  loss: 0.7309
2022/08/02 15:43:26 - mmengine - INFO - Epoch(train) [28][1100/3757]  lr: 2.4473e-06  eta: 1:58:12  time: 0.6934  data_time: 0.0182  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.0778  loss: 1.0778
2022/08/02 15:44:36 - mmengine - INFO - Epoch(train) [28][1200/3757]  lr: 2.4473e-06  eta: 1:57:02  time: 0.6998  data_time: 0.0165  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 1.0591  loss: 1.0591
2022/08/02 15:45:46 - mmengine - INFO - Epoch(train) [28][1300/3757]  lr: 2.4473e-06  eta: 1:55:52  time: 0.7046  data_time: 0.0158  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.0843  loss: 1.0843
2022/08/02 15:46:55 - mmengine - INFO - Epoch(train) [28][1400/3757]  lr: 2.4473e-06  eta: 1:54:43  time: 0.6923  data_time: 0.0167  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 0.8610  loss: 0.8610
2022/08/02 15:48:05 - mmengine - INFO - Epoch(train) [28][1500/3757]  lr: 2.4473e-06  eta: 1:53:33  time: 0.6948  data_time: 0.0155  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 0.9625  loss: 0.9625
2022/08/02 15:48:47 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 15:49:15 - mmengine - INFO - Epoch(train) [28][1600/3757]  lr: 2.4473e-06  eta: 1:52:23  time: 0.7019  data_time: 0.0174  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.0123  loss: 1.0123
2022/08/02 15:50:24 - mmengine - INFO - Epoch(train) [28][1700/3757]  lr: 2.4473e-06  eta: 1:51:13  time: 0.7008  data_time: 0.0168  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 0.9585  loss: 0.9585
2022/08/02 15:51:34 - mmengine - INFO - Epoch(train) [28][1800/3757]  lr: 2.4473e-06  eta: 1:50:04  time: 0.6928  data_time: 0.0165  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 0.8020  loss: 0.8020
2022/08/02 15:52:43 - mmengine - INFO - Epoch(train) [28][1900/3757]  lr: 2.4473e-06  eta: 1:48:54  time: 0.6957  data_time: 0.0161  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 0.9129  loss: 0.9129
2022/08/02 15:53:53 - mmengine - INFO - Epoch(train) [28][2000/3757]  lr: 2.4473e-06  eta: 1:47:44  time: 0.6964  data_time: 0.0157  memory: 45143  top1_acc: 0.6250  top5_acc: 1.0000  loss_cls: 1.0267  loss: 1.0267
2022/08/02 15:55:03 - mmengine - INFO - Epoch(train) [28][2100/3757]  lr: 2.4473e-06  eta: 1:46:34  time: 0.6968  data_time: 0.0150  memory: 45143  top1_acc: 1.0000  top5_acc: 1.0000  loss_cls: 0.9185  loss: 0.9185
2022/08/02 15:56:12 - mmengine - INFO - Epoch(train) [28][2200/3757]  lr: 2.4473e-06  eta: 1:45:25  time: 0.6957  data_time: 0.0156  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 0.9772  loss: 0.9772
2022/08/02 15:57:21 - mmengine - INFO - Epoch(train) [28][2300/3757]  lr: 2.4473e-06  eta: 1:44:15  time: 0.6903  data_time: 0.0147  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.0711  loss: 1.0711
2022/08/02 15:58:31 - mmengine - INFO - Epoch(train) [28][2400/3757]  lr: 2.4473e-06  eta: 1:43:05  time: 0.6931  data_time: 0.0160  memory: 45143  top1_acc: 0.3750  top5_acc: 0.6250  loss_cls: 1.1376  loss: 1.1376
2022/08/02 15:59:41 - mmengine - INFO - Epoch(train) [28][2500/3757]  lr: 2.4473e-06  eta: 1:41:55  time: 0.6949  data_time: 0.0153  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 0.8815  loss: 0.8815
2022/08/02 16:00:23 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 16:00:50 - mmengine - INFO - Epoch(train) [28][2600/3757]  lr: 2.4473e-06  eta: 1:40:46  time: 0.6955  data_time: 0.0157  memory: 45143  top1_acc: 0.7500  top5_acc: 0.7500  loss_cls: 1.2906  loss: 1.2906
2022/08/02 16:02:00 - mmengine - INFO - Epoch(train) [28][2700/3757]  lr: 2.4473e-06  eta: 1:39:36  time: 0.6927  data_time: 0.0156  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.0073  loss: 1.0073
2022/08/02 16:03:09 - mmengine - INFO - Epoch(train) [28][2800/3757]  lr: 2.4473e-06  eta: 1:38:26  time: 0.6932  data_time: 0.0161  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 0.8365  loss: 0.8365
2022/08/02 16:04:19 - mmengine - INFO - Epoch(train) [28][2900/3757]  lr: 2.4473e-06  eta: 1:37:16  time: 0.6916  data_time: 0.0151  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 0.9261  loss: 0.9261
2022/08/02 16:05:28 - mmengine - INFO - Epoch(train) [28][3000/3757]  lr: 2.4473e-06  eta: 1:36:07  time: 0.6972  data_time: 0.0167  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 0.6789  loss: 0.6789
2022/08/02 16:06:38 - mmengine - INFO - Epoch(train) [28][3100/3757]  lr: 2.4473e-06  eta: 1:34:57  time: 0.6955  data_time: 0.0164  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 0.9618  loss: 0.9618
2022/08/02 16:07:48 - mmengine - INFO - Epoch(train) [28][3200/3757]  lr: 2.4473e-06  eta: 1:33:47  time: 0.6995  data_time: 0.0169  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 1.0671  loss: 1.0671
2022/08/02 16:08:57 - mmengine - INFO - Epoch(train) [28][3300/3757]  lr: 2.4473e-06  eta: 1:32:37  time: 0.6963  data_time: 0.0150  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 0.9870  loss: 0.9870
2022/08/02 16:10:07 - mmengine - INFO - Epoch(train) [28][3400/3757]  lr: 2.4473e-06  eta: 1:31:28  time: 0.6994  data_time: 0.0168  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 0.8295  loss: 0.8295
2022/08/02 16:11:17 - mmengine - INFO - Epoch(train) [28][3500/3757]  lr: 2.4473e-06  eta: 1:30:18  time: 0.6946  data_time: 0.0160  memory: 45143  top1_acc: 1.0000  top5_acc: 1.0000  loss_cls: 0.7653  loss: 0.7653
2022/08/02 16:12:00 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 16:12:27 - mmengine - INFO - Epoch(train) [28][3600/3757]  lr: 2.4473e-06  eta: 1:29:08  time: 0.6947  data_time: 0.0165  memory: 45143  top1_acc: 0.5000  top5_acc: 0.7500  loss_cls: 0.7630  loss: 0.7630
2022/08/02 16:13:36 - mmengine - INFO - Epoch(train) [28][3700/3757]  lr: 2.4473e-06  eta: 1:27:58  time: 0.6996  data_time: 0.0165  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 0.8236  loss: 0.8236
2022/08/02 16:14:16 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 16:14:16 - mmengine - INFO - Epoch(train) [28][3757/3757]  lr: 2.4473e-06  eta: 1:27:31  time: 0.6822  data_time: 0.0159  memory: 45143  top1_acc: 0.8571  top5_acc: 1.0000  loss_cls: 0.7953  loss: 0.7953
2022/08/02 16:15:28 - mmengine - INFO - Epoch(train) [29][100/3757]  lr: 1.0927e-06  eta: 1:26:08  time: 0.6933  data_time: 0.0160  memory: 45143  top1_acc: 1.0000  top5_acc: 1.0000  loss_cls: 0.8825  loss: 0.8825
2022/08/02 16:16:37 - mmengine - INFO - Epoch(train) [29][200/3757]  lr: 1.0927e-06  eta: 1:24:59  time: 0.6923  data_time: 0.0156  memory: 45143  top1_acc: 0.6250  top5_acc: 1.0000  loss_cls: 1.0658  loss: 1.0658
2022/08/02 16:17:47 - mmengine - INFO - Epoch(train) [29][300/3757]  lr: 1.0927e-06  eta: 1:23:49  time: 0.7049  data_time: 0.0174  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 0.7910  loss: 0.7910
2022/08/02 16:18:57 - mmengine - INFO - Epoch(train) [29][400/3757]  lr: 1.0927e-06  eta: 1:22:39  time: 0.6983  data_time: 0.0161  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 0.8044  loss: 0.8044
2022/08/02 16:20:07 - mmengine - INFO - Epoch(train) [29][500/3757]  lr: 1.0927e-06  eta: 1:21:29  time: 0.7004  data_time: 0.0165  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 0.7815  loss: 0.7815
2022/08/02 16:21:17 - mmengine - INFO - Epoch(train) [29][600/3757]  lr: 1.0927e-06  eta: 1:20:20  time: 0.6939  data_time: 0.0162  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 0.8804  loss: 0.8804
2022/08/02 16:22:26 - mmengine - INFO - Epoch(train) [29][700/3757]  lr: 1.0927e-06  eta: 1:19:10  time: 0.6940  data_time: 0.0150  memory: 45143  top1_acc: 0.6250  top5_acc: 1.0000  loss_cls: 0.9749  loss: 0.9749
2022/08/02 16:23:36 - mmengine - INFO - Epoch(train) [29][800/3757]  lr: 1.0927e-06  eta: 1:18:00  time: 0.6910  data_time: 0.0160  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 0.9686  loss: 0.9686
2022/08/02 16:23:39 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 16:24:45 - mmengine - INFO - Epoch(train) [29][900/3757]  lr: 1.0927e-06  eta: 1:16:51  time: 0.6944  data_time: 0.0162  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 0.7648  loss: 0.7648
2022/08/02 16:25:55 - mmengine - INFO - Epoch(train) [29][1000/3757]  lr: 1.0927e-06  eta: 1:15:41  time: 0.6923  data_time: 0.0155  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 0.7364  loss: 0.7364
2022/08/02 16:27:05 - mmengine - INFO - Epoch(train) [29][1100/3757]  lr: 1.0927e-06  eta: 1:14:31  time: 0.6972  data_time: 0.0155  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.0633  loss: 1.0633
2022/08/02 16:28:14 - mmengine - INFO - Epoch(train) [29][1200/3757]  lr: 1.0927e-06  eta: 1:13:21  time: 0.6977  data_time: 0.0155  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 0.9457  loss: 0.9457
2022/08/02 16:29:24 - mmengine - INFO - Epoch(train) [29][1300/3757]  lr: 1.0927e-06  eta: 1:12:12  time: 0.6911  data_time: 0.0152  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 1.0038  loss: 1.0038
2022/08/02 16:30:34 - mmengine - INFO - Epoch(train) [29][1400/3757]  lr: 1.0927e-06  eta: 1:11:02  time: 0.6959  data_time: 0.0166  memory: 45143  top1_acc: 0.5000  top5_acc: 1.0000  loss_cls: 0.8292  loss: 0.8292
2022/08/02 16:31:43 - mmengine - INFO - Epoch(train) [29][1500/3757]  lr: 1.0927e-06  eta: 1:09:52  time: 0.6911  data_time: 0.0154  memory: 45143  top1_acc: 0.6250  top5_acc: 1.0000  loss_cls: 0.9979  loss: 0.9979
2022/08/02 16:32:53 - mmengine - INFO - Epoch(train) [29][1600/3757]  lr: 1.0927e-06  eta: 1:08:43  time: 0.6930  data_time: 0.0158  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 0.8057  loss: 0.8057
2022/08/02 16:34:03 - mmengine - INFO - Epoch(train) [29][1700/3757]  lr: 1.0927e-06  eta: 1:07:33  time: 0.6940  data_time: 0.0158  memory: 45143  top1_acc: 1.0000  top5_acc: 1.0000  loss_cls: 0.9660  loss: 0.9660
2022/08/02 16:35:13 - mmengine - INFO - Epoch(train) [29][1800/3757]  lr: 1.0927e-06  eta: 1:06:23  time: 0.6923  data_time: 0.0153  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 0.7831  loss: 0.7831
2022/08/02 16:35:16 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 16:36:23 - mmengine - INFO - Epoch(train) [29][1900/3757]  lr: 1.0927e-06  eta: 1:05:13  time: 0.6914  data_time: 0.0166  memory: 45143  top1_acc: 0.7500  top5_acc: 0.7500  loss_cls: 1.0338  loss: 1.0338
2022/08/02 16:37:32 - mmengine - INFO - Epoch(train) [29][2000/3757]  lr: 1.0927e-06  eta: 1:04:04  time: 0.6920  data_time: 0.0151  memory: 45143  top1_acc: 0.6250  top5_acc: 0.7500  loss_cls: 0.9808  loss: 0.9808
2022/08/02 16:38:42 - mmengine - INFO - Epoch(train) [29][2100/3757]  lr: 1.0927e-06  eta: 1:02:54  time: 0.6970  data_time: 0.0159  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 1.0616  loss: 1.0616
2022/08/02 16:39:52 - mmengine - INFO - Epoch(train) [29][2200/3757]  lr: 1.0927e-06  eta: 1:01:44  time: 0.6947  data_time: 0.0166  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 0.8517  loss: 0.8517
2022/08/02 16:41:02 - mmengine - INFO - Epoch(train) [29][2300/3757]  lr: 1.0927e-06  eta: 1:00:35  time: 0.6997  data_time: 0.0163  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 0.7510  loss: 0.7510
2022/08/02 16:42:11 - mmengine - INFO - Epoch(train) [29][2400/3757]  lr: 1.0927e-06  eta: 0:59:25  time: 0.6980  data_time: 0.0160  memory: 45143  top1_acc: 0.6250  top5_acc: 1.0000  loss_cls: 0.8963  loss: 0.8963
2022/08/02 16:43:21 - mmengine - INFO - Epoch(train) [29][2500/3757]  lr: 1.0927e-06  eta: 0:58:15  time: 0.6976  data_time: 0.0159  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 0.7967  loss: 0.7967
2022/08/02 16:44:31 - mmengine - INFO - Epoch(train) [29][2600/3757]  lr: 1.0927e-06  eta: 0:57:05  time: 0.7121  data_time: 0.0170  memory: 45143  top1_acc: 0.6250  top5_acc: 1.0000  loss_cls: 0.8395  loss: 0.8395
2022/08/02 16:45:41 - mmengine - INFO - Epoch(train) [29][2700/3757]  lr: 1.0927e-06  eta: 0:55:56  time: 0.6978  data_time: 0.0152  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 0.8894  loss: 0.8894
2022/08/02 16:46:50 - mmengine - INFO - Epoch(train) [29][2800/3757]  lr: 1.0927e-06  eta: 0:54:46  time: 0.6946  data_time: 0.0153  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.0913  loss: 1.0913
2022/08/02 16:46:53 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 16:48:00 - mmengine - INFO - Epoch(train) [29][2900/3757]  lr: 1.0927e-06  eta: 0:53:36  time: 0.6921  data_time: 0.0166  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 1.0896  loss: 1.0896
2022/08/02 16:49:10 - mmengine - INFO - Epoch(train) [29][3000/3757]  lr: 1.0927e-06  eta: 0:52:26  time: 0.6963  data_time: 0.0159  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 0.9399  loss: 0.9399
2022/08/02 16:50:20 - mmengine - INFO - Epoch(train) [29][3100/3757]  lr: 1.0927e-06  eta: 0:51:17  time: 0.6981  data_time: 0.0164  memory: 45143  top1_acc: 1.0000  top5_acc: 1.0000  loss_cls: 1.0981  loss: 1.0981
2022/08/02 16:51:29 - mmengine - INFO - Epoch(train) [29][3200/3757]  lr: 1.0927e-06  eta: 0:50:07  time: 0.6949  data_time: 0.0163  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 0.8546  loss: 0.8546
2022/08/02 16:52:39 - mmengine - INFO - Epoch(train) [29][3300/3757]  lr: 1.0927e-06  eta: 0:48:57  time: 0.6969  data_time: 0.0165  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 1.0327  loss: 1.0327
2022/08/02 16:53:49 - mmengine - INFO - Epoch(train) [29][3400/3757]  lr: 1.0927e-06  eta: 0:47:48  time: 0.6946  data_time: 0.0171  memory: 45143  top1_acc: 0.5000  top5_acc: 0.8750  loss_cls: 0.9748  loss: 0.9748
2022/08/02 16:54:59 - mmengine - INFO - Epoch(train) [29][3500/3757]  lr: 1.0927e-06  eta: 0:46:38  time: 0.6972  data_time: 0.0154  memory: 45143  top1_acc: 1.0000  top5_acc: 1.0000  loss_cls: 0.7414  loss: 0.7414
2022/08/02 16:56:09 - mmengine - INFO - Epoch(train) [29][3600/3757]  lr: 1.0927e-06  eta: 0:45:28  time: 0.6938  data_time: 0.0163  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 0.9366  loss: 0.9366
2022/08/02 16:57:19 - mmengine - INFO - Epoch(train) [29][3700/3757]  lr: 1.0927e-06  eta: 0:44:19  time: 0.6968  data_time: 0.0152  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 0.7940  loss: 0.7940
2022/08/02 16:57:58 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 16:57:58 - mmengine - INFO - Epoch(train) [29][3757/3757]  lr: 1.0927e-06  eta: 0:43:51  time: 0.6825  data_time: 0.0148  memory: 45143  top1_acc: 0.5714  top5_acc: 0.8571  loss_cls: 1.0284  loss: 1.0284
2022/08/02 16:58:33 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 16:59:10 - mmengine - INFO - Epoch(train) [30][100/3757]  lr: 2.7392e-07  eta: 0:42:29  time: 0.6967  data_time: 0.0163  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 0.9025  loss: 0.9025
2022/08/02 17:00:20 - mmengine - INFO - Epoch(train) [30][200/3757]  lr: 2.7392e-07  eta: 0:41:19  time: 0.6962  data_time: 0.0155  memory: 45143  top1_acc: 1.0000  top5_acc: 1.0000  loss_cls: 0.9170  loss: 0.9170
2022/08/02 17:01:29 - mmengine - INFO - Epoch(train) [30][300/3757]  lr: 2.7392e-07  eta: 0:40:09  time: 0.6925  data_time: 0.0160  memory: 45143  top1_acc: 1.0000  top5_acc: 1.0000  loss_cls: 0.7944  loss: 0.7944
2022/08/02 17:02:38 - mmengine - INFO - Epoch(train) [30][400/3757]  lr: 2.7392e-07  eta: 0:39:00  time: 0.6911  data_time: 0.0153  memory: 45143  top1_acc: 0.3750  top5_acc: 0.7500  loss_cls: 1.0523  loss: 1.0523
2022/08/02 17:03:48 - mmengine - INFO - Epoch(train) [30][500/3757]  lr: 2.7392e-07  eta: 0:37:50  time: 0.6944  data_time: 0.0153  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 0.9914  loss: 0.9914
2022/08/02 17:04:58 - mmengine - INFO - Epoch(train) [30][600/3757]  lr: 2.7392e-07  eta: 0:36:40  time: 0.6947  data_time: 0.0156  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.1115  loss: 1.1115
2022/08/02 17:06:08 - mmengine - INFO - Epoch(train) [30][700/3757]  lr: 2.7392e-07  eta: 0:35:30  time: 0.6938  data_time: 0.0154  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 0.7480  loss: 0.7480
2022/08/02 17:07:17 - mmengine - INFO - Epoch(train) [30][800/3757]  lr: 2.7392e-07  eta: 0:34:21  time: 0.6952  data_time: 0.0149  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 0.9782  loss: 0.9782
2022/08/02 17:08:27 - mmengine - INFO - Epoch(train) [30][900/3757]  lr: 2.7392e-07  eta: 0:33:11  time: 0.6934  data_time: 0.0157  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 0.9224  loss: 0.9224
2022/08/02 17:09:37 - mmengine - INFO - Epoch(train) [30][1000/3757]  lr: 2.7392e-07  eta: 0:32:01  time: 0.6914  data_time: 0.0157  memory: 45143  top1_acc: 0.6250  top5_acc: 1.0000  loss_cls: 0.7691  loss: 0.7691
2022/08/02 17:10:09 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 17:10:46 - mmengine - INFO - Epoch(train) [30][1100/3757]  lr: 2.7392e-07  eta: 0:30:52  time: 0.6921  data_time: 0.0154  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.0642  loss: 1.0642
2022/08/02 17:11:56 - mmengine - INFO - Epoch(train) [30][1200/3757]  lr: 2.7392e-07  eta: 0:29:42  time: 0.6944  data_time: 0.0146  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 0.8580  loss: 0.8580
2022/08/02 17:13:05 - mmengine - INFO - Epoch(train) [30][1300/3757]  lr: 2.7392e-07  eta: 0:28:32  time: 0.6936  data_time: 0.0163  memory: 45143  top1_acc: 1.0000  top5_acc: 1.0000  loss_cls: 0.8298  loss: 0.8298
2022/08/02 17:14:15 - mmengine - INFO - Epoch(train) [30][1400/3757]  lr: 2.7392e-07  eta: 0:27:22  time: 0.6918  data_time: 0.0148  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.3052  loss: 1.3052
2022/08/02 17:15:25 - mmengine - INFO - Epoch(train) [30][1500/3757]  lr: 2.7392e-07  eta: 0:26:13  time: 0.6974  data_time: 0.0162  memory: 45143  top1_acc: 1.0000  top5_acc: 1.0000  loss_cls: 0.8330  loss: 0.8330
2022/08/02 17:16:35 - mmengine - INFO - Epoch(train) [30][1600/3757]  lr: 2.7392e-07  eta: 0:25:03  time: 0.6937  data_time: 0.0155  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 0.7681  loss: 0.7681
2022/08/02 17:17:44 - mmengine - INFO - Epoch(train) [30][1700/3757]  lr: 2.7392e-07  eta: 0:23:53  time: 0.6921  data_time: 0.0167  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 0.9524  loss: 0.9524
2022/08/02 17:18:54 - mmengine - INFO - Epoch(train) [30][1800/3757]  lr: 2.7392e-07  eta: 0:22:44  time: 0.6926  data_time: 0.0159  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 0.7302  loss: 0.7302
2022/08/02 17:20:03 - mmengine - INFO - Epoch(train) [30][1900/3757]  lr: 2.7392e-07  eta: 0:21:34  time: 0.6973  data_time: 0.0161  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 1.0001  loss: 1.0001
2022/08/02 17:21:13 - mmengine - INFO - Epoch(train) [30][2000/3757]  lr: 2.7392e-07  eta: 0:20:24  time: 0.6963  data_time: 0.0161  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 0.9499  loss: 0.9499
2022/08/02 17:21:46 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 17:22:22 - mmengine - INFO - Epoch(train) [30][2100/3757]  lr: 2.7392e-07  eta: 0:19:15  time: 0.6936  data_time: 0.0152  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 0.8497  loss: 0.8497
2022/08/02 17:23:32 - mmengine - INFO - Epoch(train) [30][2200/3757]  lr: 2.7392e-07  eta: 0:18:05  time: 0.6947  data_time: 0.0156  memory: 45143  top1_acc: 0.6250  top5_acc: 0.8750  loss_cls: 1.0065  loss: 1.0065
2022/08/02 17:24:41 - mmengine - INFO - Epoch(train) [30][2300/3757]  lr: 2.7392e-07  eta: 0:16:55  time: 0.6902  data_time: 0.0149  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 0.9330  loss: 0.9330
2022/08/02 17:25:51 - mmengine - INFO - Epoch(train) [30][2400/3757]  lr: 2.7392e-07  eta: 0:15:45  time: 0.6920  data_time: 0.0161  memory: 45143  top1_acc: 0.8750  top5_acc: 0.8750  loss_cls: 0.8964  loss: 0.8964
2022/08/02 17:27:00 - mmengine - INFO - Epoch(train) [30][2500/3757]  lr: 2.7392e-07  eta: 0:14:36  time: 0.6918  data_time: 0.0147  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 0.7865  loss: 0.7865
2022/08/02 17:28:10 - mmengine - INFO - Epoch(train) [30][2600/3757]  lr: 2.7392e-07  eta: 0:13:26  time: 0.6938  data_time: 0.0154  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 0.7122  loss: 0.7122
2022/08/02 17:29:20 - mmengine - INFO - Epoch(train) [30][2700/3757]  lr: 2.7392e-07  eta: 0:12:16  time: 0.6938  data_time: 0.0150  memory: 45143  top1_acc: 0.7500  top5_acc: 0.7500  loss_cls: 1.0487  loss: 1.0487
2022/08/02 17:30:29 - mmengine - INFO - Epoch(train) [30][2800/3757]  lr: 2.7392e-07  eta: 0:11:07  time: 0.6921  data_time: 0.0156  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 0.8421  loss: 0.8421
2022/08/02 17:31:39 - mmengine - INFO - Epoch(train) [30][2900/3757]  lr: 2.7392e-07  eta: 0:09:57  time: 0.6905  data_time: 0.0147  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 1.1352  loss: 1.1352
2022/08/02 17:32:48 - mmengine - INFO - Epoch(train) [30][3000/3757]  lr: 2.7392e-07  eta: 0:08:47  time: 0.6930  data_time: 0.0158  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 0.9958  loss: 0.9958
2022/08/02 17:33:21 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 17:33:58 - mmengine - INFO - Epoch(train) [30][3100/3757]  lr: 2.7392e-07  eta: 0:07:37  time: 0.6914  data_time: 0.0148  memory: 45143  top1_acc: 0.7500  top5_acc: 1.0000  loss_cls: 0.9356  loss: 0.9356
2022/08/02 17:35:07 - mmengine - INFO - Epoch(train) [30][3200/3757]  lr: 2.7392e-07  eta: 0:06:28  time: 0.6975  data_time: 0.0159  memory: 45143  top1_acc: 1.0000  top5_acc: 1.0000  loss_cls: 0.9796  loss: 0.9796
2022/08/02 17:36:17 - mmengine - INFO - Epoch(train) [30][3300/3757]  lr: 2.7392e-07  eta: 0:05:18  time: 0.6921  data_time: 0.0159  memory: 45143  top1_acc: 0.6250  top5_acc: 1.0000  loss_cls: 1.0474  loss: 1.0474
2022/08/02 17:37:27 - mmengine - INFO - Epoch(train) [30][3400/3757]  lr: 2.7392e-07  eta: 0:04:08  time: 0.6973  data_time: 0.0156  memory: 45143  top1_acc: 1.0000  top5_acc: 1.0000  loss_cls: 0.8456  loss: 0.8456
2022/08/02 17:38:37 - mmengine - INFO - Epoch(train) [30][3500/3757]  lr: 2.7392e-07  eta: 0:02:59  time: 0.6998  data_time: 0.0163  memory: 45143  top1_acc: 0.6250  top5_acc: 1.0000  loss_cls: 0.8587  loss: 0.8587
2022/08/02 17:39:47 - mmengine - INFO - Epoch(train) [30][3600/3757]  lr: 2.7392e-07  eta: 0:01:49  time: 0.6939  data_time: 0.0161  memory: 45143  top1_acc: 0.7500  top5_acc: 0.8750  loss_cls: 0.9399  loss: 0.9399
2022/08/02 17:40:56 - mmengine - INFO - Epoch(train) [30][3700/3757]  lr: 2.7392e-07  eta: 0:00:39  time: 0.6954  data_time: 0.0171  memory: 45143  top1_acc: 0.8750  top5_acc: 1.0000  loss_cls: 0.9142  loss: 0.9142
2022/08/02 17:41:36 - mmengine - INFO - Exp name: swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb_20220801_192856
2022/08/02 17:41:36 - mmengine - INFO - Epoch(train) [30][3757/3757]  lr: 2.7392e-07  eta: 0:00:11  time: 0.6967  data_time: 0.0164  memory: 45143  top1_acc: 0.8571  top5_acc: 1.0000  loss_cls: 0.8038  loss: 0.8038
2022/08/02 17:41:36 - mmengine - INFO - Saving checkpoint at 30 epochs
2022/08/02 17:44:55 - mmengine - INFO - Epoch(val) [30][100/310]    eta: 0:01:15  time: 0.3606  data_time: 0.1084  memory: 8742  
2022/08/02 17:45:22 - mmengine - INFO - Epoch(val) [30][200/310]    eta: 0:00:28  time: 0.2607  data_time: 0.0085  memory: 8742  
2022/08/02 17:45:48 - mmengine - INFO - Epoch(val) [30][300/310]    eta: 0:00:02  time: 0.2660  data_time: 0.0095  memory: 8742  
2022/08/02 17:45:54 - mmengine - INFO - Epoch(val) [30][310/310]  acc/top1: 0.7546  acc/top5: 0.9162  acc/mean1: 0.7545
2022/08/02 17:45:54 - mmengine - INFO - The previous best checkpoint /mnt/lustre/daiwenxun/X/mmaction2/work_dirs/swin_base_imagenet_1k_pretrained_32x2x1_30e_8xb8_kinetics400_rgb/best_acc/top1_epoch_28.pth is removed
2022/08/02 17:46:23 - mmengine - INFO - The best checkpoint with 0.7546 acc/top1 at 31 epoch is saved to best_acc/top1_epoch_31.pth.