diff --git "a/laion_cc3m/out.log" "b/laion_cc3m/out.log" new file mode 100644--- /dev/null +++ "b/laion_cc3m/out.log" @@ -0,0 +1,1352 @@ +2023-04-03,18:34:49 | INFO | Running in distributed mode with multiple processes. Device: cuda:0.Process (global: 0, local 0), total 4. +2023-04-03,18:34:49 | INFO | Loaded coca_ViT-L-14 model config. +2023-04-03,18:36:58 | INFO | Loading pretrained coca_ViT-L-14 weights (laion2B-s13B-b90k). +2023-04-03,18:37:03 | INFO | Model: +2023-04-03,18:37:03 | INFO | CoCa( + (text): TextTransformer( + (token_embedding): Embedding(49408, 768) + (transformer): Transformer( + (resblocks): ModuleList( + (0): ResidualAttentionBlock( + (ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True) + ) + (ls_1): Identity() + (ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=768, out_features=3072, bias=True) + (gelu): GELU() + (c_proj): Linear(in_features=3072, out_features=768, bias=True) + ) + (ls_2): Identity() + ) + (1): ResidualAttentionBlock( + (ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True) + ) + (ls_1): Identity() + (ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=768, out_features=3072, bias=True) + (gelu): GELU() + (c_proj): Linear(in_features=3072, out_features=768, bias=True) + ) + (ls_2): Identity() + ) + (2): ResidualAttentionBlock( + (ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True) + ) + (ls_1): Identity() + (ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=768, out_features=3072, bias=True) + (gelu): GELU() + (c_proj): Linear(in_features=3072, out_features=768, bias=True) + ) + (ls_2): Identity() + ) + (3): ResidualAttentionBlock( + (ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True) + ) + (ls_1): Identity() + (ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=768, out_features=3072, bias=True) + (gelu): GELU() + (c_proj): Linear(in_features=3072, out_features=768, bias=True) + ) + (ls_2): Identity() + ) + (4): ResidualAttentionBlock( + (ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True) + ) + (ls_1): Identity() + (ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=768, out_features=3072, bias=True) + (gelu): GELU() + (c_proj): Linear(in_features=3072, out_features=768, bias=True) + ) + (ls_2): Identity() + ) + (5): ResidualAttentionBlock( + (ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True) + ) + (ls_1): Identity() + (ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=768, out_features=3072, bias=True) + (gelu): GELU() + (c_proj): Linear(in_features=3072, out_features=768, bias=True) + ) + (ls_2): Identity() + ) + (6): ResidualAttentionBlock( + (ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True) + ) + (ls_1): Identity() + (ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=768, out_features=3072, bias=True) + (gelu): GELU() + (c_proj): Linear(in_features=3072, out_features=768, bias=True) + ) + (ls_2): Identity() + ) + (7): ResidualAttentionBlock( + (ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True) + ) + (ls_1): Identity() + (ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=768, out_features=3072, bias=True) + (gelu): GELU() + (c_proj): Linear(in_features=3072, out_features=768, bias=True) + ) + (ls_2): Identity() + ) + (8): ResidualAttentionBlock( + (ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True) + ) + (ls_1): Identity() + (ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=768, out_features=3072, bias=True) + (gelu): GELU() + (c_proj): Linear(in_features=3072, out_features=768, bias=True) + ) + (ls_2): Identity() + ) + (9): ResidualAttentionBlock( + (ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True) + ) + (ls_1): Identity() + (ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=768, out_features=3072, bias=True) + (gelu): GELU() + (c_proj): Linear(in_features=3072, out_features=768, bias=True) + ) + (ls_2): Identity() + ) + (10): ResidualAttentionBlock( + (ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True) + ) + (ls_1): Identity() + (ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=768, out_features=3072, bias=True) + (gelu): GELU() + (c_proj): Linear(in_features=3072, out_features=768, bias=True) + ) + (ls_2): Identity() + ) + (11): ResidualAttentionBlock( + (ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True) + ) + (ls_1): Identity() + (ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=768, out_features=3072, bias=True) + (gelu): GELU() + (c_proj): Linear(in_features=3072, out_features=768, bias=True) + ) + (ls_2): Identity() + ) + ) + ) + (ln_final): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + ) + (visual): VisionTransformer( + (patchnorm_pre_ln): Identity() + (conv1): Conv2d(3, 1024, kernel_size=(14, 14), stride=(14, 14), bias=False) + (patch_dropout): Identity() + (ln_pre): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (transformer): Transformer( + (resblocks): ModuleList( + (0): ResidualAttentionBlock( + (ln_1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True) + ) + (ls_1): Identity() + (ln_2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=1024, out_features=4096, bias=True) + (gelu): GELU() + (c_proj): Linear(in_features=4096, out_features=1024, bias=True) + ) + (ls_2): Identity() + ) + (1): ResidualAttentionBlock( + (ln_1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True) + ) + (ls_1): Identity() + (ln_2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=1024, out_features=4096, bias=True) + (gelu): GELU() + (c_proj): Linear(in_features=4096, out_features=1024, bias=True) + ) + (ls_2): Identity() + ) + (2): ResidualAttentionBlock( + (ln_1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True) + ) + (ls_1): Identity() + (ln_2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=1024, out_features=4096, bias=True) + (gelu): GELU() + (c_proj): Linear(in_features=4096, out_features=1024, bias=True) + ) + (ls_2): Identity() + ) + (3): ResidualAttentionBlock( + (ln_1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True) + ) + (ls_1): Identity() + (ln_2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=1024, out_features=4096, bias=True) + (gelu): GELU() + (c_proj): Linear(in_features=4096, out_features=1024, bias=True) + ) + (ls_2): Identity() + ) + (4): ResidualAttentionBlock( + (ln_1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True) + ) + (ls_1): Identity() + (ln_2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=1024, out_features=4096, bias=True) + (gelu): GELU() + (c_proj): Linear(in_features=4096, out_features=1024, bias=True) + ) + (ls_2): Identity() + ) + (5): ResidualAttentionBlock( + (ln_1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True) + ) + (ls_1): Identity() + (ln_2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=1024, out_features=4096, bias=True) + (gelu): GELU() + (c_proj): Linear(in_features=4096, out_features=1024, bias=True) + ) + (ls_2): Identity() + ) + (6): ResidualAttentionBlock( + (ln_1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True) + ) + (ls_1): Identity() + (ln_2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=1024, out_features=4096, bias=True) + (gelu): GELU() + (c_proj): Linear(in_features=4096, out_features=1024, bias=True) + ) + (ls_2): Identity() + ) + (7): ResidualAttentionBlock( + (ln_1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True) + ) + (ls_1): Identity() + (ln_2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=1024, out_features=4096, bias=True) + (gelu): GELU() + (c_proj): Linear(in_features=4096, out_features=1024, bias=True) + ) + (ls_2): Identity() + ) + (8): ResidualAttentionBlock( + (ln_1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True) + ) + (ls_1): Identity() + (ln_2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=1024, out_features=4096, bias=True) + (gelu): GELU() + (c_proj): Linear(in_features=4096, out_features=1024, bias=True) + ) + (ls_2): Identity() + ) + (9): ResidualAttentionBlock( + (ln_1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True) + ) + (ls_1): Identity() + (ln_2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=1024, out_features=4096, bias=True) + (gelu): GELU() + (c_proj): Linear(in_features=4096, out_features=1024, bias=True) + ) + (ls_2): Identity() + ) + (10): ResidualAttentionBlock( + (ln_1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True) + ) + (ls_1): Identity() + (ln_2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=1024, out_features=4096, bias=True) + (gelu): GELU() + (c_proj): Linear(in_features=4096, out_features=1024, bias=True) + ) + (ls_2): Identity() + ) + (11): ResidualAttentionBlock( + (ln_1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True) + ) + (ls_1): Identity() + (ln_2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=1024, out_features=4096, bias=True) + (gelu): GELU() + (c_proj): Linear(in_features=4096, out_features=1024, bias=True) + ) + (ls_2): Identity() + ) + (12): ResidualAttentionBlock( + (ln_1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True) + ) + (ls_1): Identity() + (ln_2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=1024, out_features=4096, bias=True) + (gelu): GELU() + (c_proj): Linear(in_features=4096, out_features=1024, bias=True) + ) + (ls_2): Identity() + ) + (13): ResidualAttentionBlock( + (ln_1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True) + ) + (ls_1): Identity() + (ln_2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=1024, out_features=4096, bias=True) + (gelu): GELU() + (c_proj): Linear(in_features=4096, out_features=1024, bias=True) + ) + (ls_2): Identity() + ) + (14): ResidualAttentionBlock( + (ln_1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True) + ) + (ls_1): Identity() + (ln_2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=1024, out_features=4096, bias=True) + (gelu): GELU() + (c_proj): Linear(in_features=4096, out_features=1024, bias=True) + ) + (ls_2): Identity() + ) + (15): ResidualAttentionBlock( + (ln_1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True) + ) + (ls_1): Identity() + (ln_2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=1024, out_features=4096, bias=True) + (gelu): GELU() + (c_proj): Linear(in_features=4096, out_features=1024, bias=True) + ) + (ls_2): Identity() + ) + (16): ResidualAttentionBlock( + (ln_1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True) + ) + (ls_1): Identity() + (ln_2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=1024, out_features=4096, bias=True) + (gelu): GELU() + (c_proj): Linear(in_features=4096, out_features=1024, bias=True) + ) + (ls_2): Identity() + ) + (17): ResidualAttentionBlock( + (ln_1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True) + ) + (ls_1): Identity() + (ln_2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=1024, out_features=4096, bias=True) + (gelu): GELU() + (c_proj): Linear(in_features=4096, out_features=1024, bias=True) + ) + (ls_2): Identity() + ) + (18): ResidualAttentionBlock( + (ln_1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True) + ) + (ls_1): Identity() + (ln_2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=1024, out_features=4096, bias=True) + (gelu): GELU() + (c_proj): Linear(in_features=4096, out_features=1024, bias=True) + ) + (ls_2): Identity() + ) + (19): ResidualAttentionBlock( + (ln_1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True) + ) + (ls_1): Identity() + (ln_2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=1024, out_features=4096, bias=True) + (gelu): GELU() + (c_proj): Linear(in_features=4096, out_features=1024, bias=True) + ) + (ls_2): Identity() + ) + (20): ResidualAttentionBlock( + (ln_1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True) + ) + (ls_1): Identity() + (ln_2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=1024, out_features=4096, bias=True) + (gelu): GELU() + (c_proj): Linear(in_features=4096, out_features=1024, bias=True) + ) + (ls_2): Identity() + ) + (21): ResidualAttentionBlock( + (ln_1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True) + ) + (ls_1): Identity() + (ln_2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=1024, out_features=4096, bias=True) + (gelu): GELU() + (c_proj): Linear(in_features=4096, out_features=1024, bias=True) + ) + (ls_2): Identity() + ) + (22): ResidualAttentionBlock( + (ln_1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True) + ) + (ls_1): Identity() + (ln_2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=1024, out_features=4096, bias=True) + (gelu): GELU() + (c_proj): Linear(in_features=4096, out_features=1024, bias=True) + ) + (ls_2): Identity() + ) + (23): ResidualAttentionBlock( + (ln_1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True) + ) + (ls_1): Identity() + (ln_2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=1024, out_features=4096, bias=True) + (gelu): GELU() + (c_proj): Linear(in_features=4096, out_features=1024, bias=True) + ) + (ls_2): Identity() + ) + ) + ) + (attn_pool): AttentionalPooler( + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True) + ) + (ln_q): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (ln_k): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + ) + (ln_post): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + ) + (text_decoder): MultimodalTransformer( + (resblocks): ModuleList( + (0): ResidualAttentionBlock( + (ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True) + ) + (ls_1): Identity() + (ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=768, out_features=3072, bias=True) + (gelu): GELU() + (c_proj): Linear(in_features=3072, out_features=768, bias=True) + ) + (ls_2): Identity() + ) + (1): ResidualAttentionBlock( + (ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True) + ) + (ls_1): Identity() + (ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=768, out_features=3072, bias=True) + (gelu): GELU() + (c_proj): Linear(in_features=3072, out_features=768, bias=True) + ) + (ls_2): Identity() + ) + (2): ResidualAttentionBlock( + (ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True) + ) + (ls_1): Identity() + (ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=768, out_features=3072, bias=True) + (gelu): GELU() + (c_proj): Linear(in_features=3072, out_features=768, bias=True) + ) + (ls_2): Identity() + ) + (3): ResidualAttentionBlock( + (ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True) + ) + (ls_1): Identity() + (ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=768, out_features=3072, bias=True) + (gelu): GELU() + (c_proj): Linear(in_features=3072, out_features=768, bias=True) + ) + (ls_2): Identity() + ) + (4): ResidualAttentionBlock( + (ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True) + ) + (ls_1): Identity() + (ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=768, out_features=3072, bias=True) + (gelu): GELU() + (c_proj): Linear(in_features=3072, out_features=768, bias=True) + ) + (ls_2): Identity() + ) + (5): ResidualAttentionBlock( + (ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True) + ) + (ls_1): Identity() + (ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=768, out_features=3072, bias=True) + (gelu): GELU() + (c_proj): Linear(in_features=3072, out_features=768, bias=True) + ) + (ls_2): Identity() + ) + (6): ResidualAttentionBlock( + (ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True) + ) + (ls_1): Identity() + (ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=768, out_features=3072, bias=True) + (gelu): GELU() + (c_proj): Linear(in_features=3072, out_features=768, bias=True) + ) + (ls_2): Identity() + ) + (7): ResidualAttentionBlock( + (ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True) + ) + (ls_1): Identity() + (ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=768, out_features=3072, bias=True) + (gelu): GELU() + (c_proj): Linear(in_features=3072, out_features=768, bias=True) + ) + (ls_2): Identity() + ) + (8): ResidualAttentionBlock( + (ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True) + ) + (ls_1): Identity() + (ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=768, out_features=3072, bias=True) + (gelu): GELU() + (c_proj): Linear(in_features=3072, out_features=768, bias=True) + ) + (ls_2): Identity() + ) + (9): ResidualAttentionBlock( + (ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True) + ) + (ls_1): Identity() + (ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=768, out_features=3072, bias=True) + (gelu): GELU() + (c_proj): Linear(in_features=3072, out_features=768, bias=True) + ) + (ls_2): Identity() + ) + (10): ResidualAttentionBlock( + (ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True) + ) + (ls_1): Identity() + (ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=768, out_features=3072, bias=True) + (gelu): GELU() + (c_proj): Linear(in_features=3072, out_features=768, bias=True) + ) + (ls_2): Identity() + ) + (11): ResidualAttentionBlock( + (ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True) + ) + (ls_1): Identity() + (ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=768, out_features=3072, bias=True) + (gelu): GELU() + (c_proj): Linear(in_features=3072, out_features=768, bias=True) + ) + (ls_2): Identity() + ) + ) + (cross_attn): ModuleList( + (0): ResidualAttentionBlock( + (ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True) + ) + (ls_1): Identity() + (ln_1_kv): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=768, out_features=3072, bias=True) + (gelu): GELU() + (c_proj): Linear(in_features=3072, out_features=768, bias=True) + ) + (ls_2): Identity() + ) + (1): ResidualAttentionBlock( + (ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True) + ) + (ls_1): Identity() + (ln_1_kv): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=768, out_features=3072, bias=True) + (gelu): GELU() + (c_proj): Linear(in_features=3072, out_features=768, bias=True) + ) + (ls_2): Identity() + ) + (2): ResidualAttentionBlock( + (ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True) + ) + (ls_1): Identity() + (ln_1_kv): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=768, out_features=3072, bias=True) + (gelu): GELU() + (c_proj): Linear(in_features=3072, out_features=768, bias=True) + ) + (ls_2): Identity() + ) + (3): ResidualAttentionBlock( + (ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True) + ) + (ls_1): Identity() + (ln_1_kv): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=768, out_features=3072, bias=True) + (gelu): GELU() + (c_proj): Linear(in_features=3072, out_features=768, bias=True) + ) + (ls_2): Identity() + ) + (4): ResidualAttentionBlock( + (ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True) + ) + (ls_1): Identity() + (ln_1_kv): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=768, out_features=3072, bias=True) + (gelu): GELU() + (c_proj): Linear(in_features=3072, out_features=768, bias=True) + ) + (ls_2): Identity() + ) + (5): ResidualAttentionBlock( + (ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True) + ) + (ls_1): Identity() + (ln_1_kv): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=768, out_features=3072, bias=True) + (gelu): GELU() + (c_proj): Linear(in_features=3072, out_features=768, bias=True) + ) + (ls_2): Identity() + ) + (6): ResidualAttentionBlock( + (ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True) + ) + (ls_1): Identity() + (ln_1_kv): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=768, out_features=3072, bias=True) + (gelu): GELU() + (c_proj): Linear(in_features=3072, out_features=768, bias=True) + ) + (ls_2): Identity() + ) + (7): ResidualAttentionBlock( + (ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True) + ) + (ls_1): Identity() + (ln_1_kv): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=768, out_features=3072, bias=True) + (gelu): GELU() + (c_proj): Linear(in_features=3072, out_features=768, bias=True) + ) + (ls_2): Identity() + ) + (8): ResidualAttentionBlock( + (ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True) + ) + (ls_1): Identity() + (ln_1_kv): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=768, out_features=3072, bias=True) + (gelu): GELU() + (c_proj): Linear(in_features=3072, out_features=768, bias=True) + ) + (ls_2): Identity() + ) + (9): ResidualAttentionBlock( + (ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True) + ) + (ls_1): Identity() + (ln_1_kv): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=768, out_features=3072, bias=True) + (gelu): GELU() + (c_proj): Linear(in_features=3072, out_features=768, bias=True) + ) + (ls_2): Identity() + ) + (10): ResidualAttentionBlock( + (ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True) + ) + (ls_1): Identity() + (ln_1_kv): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=768, out_features=3072, bias=True) + (gelu): GELU() + (c_proj): Linear(in_features=3072, out_features=768, bias=True) + ) + (ls_2): Identity() + ) + (11): ResidualAttentionBlock( + (ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True) + ) + (ls_1): Identity() + (ln_1_kv): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + (mlp): Sequential( + (c_fc): Linear(in_features=768, out_features=3072, bias=True) + (gelu): GELU() + (c_proj): Linear(in_features=3072, out_features=768, bias=True) + ) + (ls_2): Identity() + ) + ) + (ln_final): LayerNorm((768,), eps=1e-05, elementwise_affine=True) + ) +) +2023-04-03,18:37:03 | INFO | Params: +2023-04-03,18:37:03 | INFO | accum_freq: 1 +2023-04-03,18:37:03 | INFO | aug_cfg: {} +2023-04-03,18:37:03 | INFO | batch_size: 16 +2023-04-03,18:37:03 | INFO | beta1: 0.9 +2023-04-03,18:37:03 | INFO | beta2: 0.98 +2023-04-03,18:37:03 | INFO | checkpoint_path: ./logs/2023_04_03-18_34_41-model_coca_ViT-L-14-lr_1e-05-b_16-j_4-p_amp/checkpoints +2023-04-03,18:37:03 | INFO | coca_caption_loss_weight: 2.0 +2023-04-03,18:37:03 | INFO | coca_contrastive_loss_weight: 1.0 +2023-04-03,18:37:03 | INFO | copy_codebase: False +2023-04-03,18:37:03 | INFO | csv_caption_key: title +2023-04-03,18:37:03 | INFO | csv_img_key: filepath +2023-04-03,18:37:03 | INFO | csv_separator: +2023-04-03,18:37:03 | INFO | dataset_resampled: False +2023-04-03,18:37:03 | INFO | dataset_type: webdataset +2023-04-03,18:37:03 | INFO | ddp_static_graph: False +2023-04-03,18:37:03 | INFO | debug: False +2023-04-03,18:37:03 | INFO | delete_previous_checkpoint: False +2023-04-03,18:37:03 | INFO | device: cuda:0 +2023-04-03,18:37:03 | INFO | dist_backend: nccl +2023-04-03,18:37:03 | INFO | dist_url: env:// +2023-04-03,18:37:03 | INFO | distill: False +2023-04-03,18:37:03 | INFO | distill_model: None +2023-04-03,18:37:03 | INFO | distill_pretrained: None +2023-04-03,18:37:03 | INFO | distributed: True +2023-04-03,18:37:03 | INFO | epochs: 1 +2023-04-03,18:37:03 | INFO | epochs_cooldown: None +2023-04-03,18:37:03 | INFO | eps: 1e-06 +2023-04-03,18:37:03 | INFO | force_custom_text: False +2023-04-03,18:37:03 | INFO | force_image_size: None +2023-04-03,18:37:03 | INFO | force_patch_dropout: None +2023-04-03,18:37:03 | INFO | force_quick_gelu: False +2023-04-03,18:37:03 | INFO | gather_with_grad: False +2023-04-03,18:37:03 | INFO | grad_checkpointing: False +2023-04-03,18:37:03 | INFO | grad_clip_norm: None +2023-04-03,18:37:03 | INFO | horovod: False +2023-04-03,18:37:03 | INFO | image_mean: None +2023-04-03,18:37:03 | INFO | image_std: None +2023-04-03,18:37:03 | INFO | imagenet_v2: None +2023-04-03,18:37:03 | INFO | imagenet_val: None +2023-04-03,18:37:03 | INFO | local_loss: False +2023-04-03,18:37:03 | INFO | local_rank: 0 +2023-04-03,18:37:03 | INFO | lock_image: False +2023-04-03,18:37:03 | INFO | lock_image_freeze_bn_stats: False +2023-04-03,18:37:03 | INFO | lock_image_unlocked_groups: 0 +2023-04-03,18:37:03 | INFO | lock_text: False +2023-04-03,18:37:03 | INFO | lock_text_freeze_layer_norm: False +2023-04-03,18:37:03 | INFO | lock_text_unlocked_layers: 0 +2023-04-03,18:37:03 | INFO | log_every_n_steps: 100 +2023-04-03,18:37:03 | INFO | log_level: 20 +2023-04-03,18:37:03 | INFO | log_local: False +2023-04-03,18:37:03 | INFO | log_path: ./logs/2023_04_03-18_34_41-model_coca_ViT-L-14-lr_1e-05-b_16-j_4-p_amp/out.log +2023-04-03,18:37:03 | INFO | logs: ./logs/ +2023-04-03,18:37:03 | INFO | lr: 1e-05 +2023-04-03,18:37:03 | INFO | lr_cooldown_end: 0.0 +2023-04-03,18:37:03 | INFO | lr_cooldown_power: 1.0 +2023-04-03,18:37:03 | INFO | lr_scheduler: cosine +2023-04-03,18:37:03 | INFO | model: coca_ViT-L-14 +2023-04-03,18:37:03 | INFO | name: 2023_04_03-18_34_41-model_coca_ViT-L-14-lr_1e-05-b_16-j_4-p_amp +2023-04-03,18:37:03 | INFO | no_set_device_rank: False +2023-04-03,18:37:03 | INFO | precision: amp +2023-04-03,18:37:03 | INFO | pretrained: laion2B-s13B-b90k +2023-04-03,18:37:03 | INFO | pretrained_image: False +2023-04-03,18:37:03 | INFO | rank: 0 +2023-04-03,18:37:03 | INFO | remote_sync: None +2023-04-03,18:37:03 | INFO | remote_sync_frequency: 300 +2023-04-03,18:37:03 | INFO | remote_sync_protocol: s3 +2023-04-03,18:37:03 | INFO | report_to: +2023-04-03,18:37:03 | INFO | resume: None +2023-04-03,18:37:03 | INFO | save_frequency: 1 +2023-04-03,18:37:03 | INFO | save_most_recent: False +2023-04-03,18:37:03 | INFO | seed: 0 +2023-04-03,18:37:03 | INFO | skip_scheduler: False +2023-04-03,18:37:03 | INFO | tensorboard: False +2023-04-03,18:37:03 | INFO | tensorboard_path: +2023-04-03,18:37:03 | INFO | torchscript: False +2023-04-03,18:37:03 | INFO | trace: False +2023-04-03,18:37:03 | INFO | train_data: /home/vision/seonghoon/caption_dataset/cc3m/{00000..00331}.tar +2023-04-03,18:37:03 | INFO | train_data_upsampling_factors: None +2023-04-03,18:37:03 | INFO | train_num_samples: 2339077 +2023-04-03,18:37:03 | INFO | use_bn_sync: False +2023-04-03,18:37:03 | INFO | val_data: None +2023-04-03,18:37:03 | INFO | val_frequency: 1 +2023-04-03,18:37:03 | INFO | val_num_samples: None +2023-04-03,18:37:03 | INFO | wandb: False +2023-04-03,18:37:03 | INFO | wandb_notes: +2023-04-03,18:37:03 | INFO | wandb_project_name: open-clip +2023-04-03,18:37:03 | INFO | warmup: 1000 +2023-04-03,18:37:03 | INFO | wd: 0.1 +2023-04-03,18:37:03 | INFO | workers: 4 +2023-04-03,18:37:03 | INFO | world_size: 4 +2023-04-03,18:37:03 | INFO | zeroshot_frequency: 2 +2023-04-03,18:37:03 | INFO | Start epoch 0 +2023-04-03,18:37:08 | INFO | Train Epoch: 0 [ 64/2339328 (0%)] Data (t): 1.630 Batch (t): 4.533, 14.1195/s LR: 0.000000 Logit Scale: 100.000 Contrastive_loss: 0.46120 (0.46120) Caption_loss: 8.1342 (8.1342) Loss: 8.5954 (8.5954) +2023-04-03,18:37:08 | INFO | Reducer buckets have been rebuilt in this iteration. +2023-04-03,18:38:41 | INFO | Train Epoch: 0 [ 6464/2339328 (0%)] Data (t): 0.033 Batch (t): 0.930, 67.7508/s LR: 0.000001 Logit Scale: 99.996 Contrastive_loss: 0.23321 (0.34720) Caption_loss: 5.3161 (6.7251) Loss: 5.5493 (7.0723) +2023-04-03,18:40:15 | INFO | Train Epoch: 0 [ 12864/2339328 (1%)] Data (t): 0.035 Batch (t): 0.947, 69.1049/s LR: 0.000002 Logit Scale: 99.983 Contrastive_loss: 0.012901 (0.23577) Caption_loss: 4.9327 (6.1276) Loss: 4.9456 (6.3634) +2023-04-03,18:41:50 | INFO | Train Epoch: 0 [ 19264/2339328 (1%)] Data (t): 0.035 Batch (t): 0.948, 65.0821/s LR: 0.000003 Logit Scale: 99.967 Contrastive_loss: 0.20268 (0.22750) Caption_loss: 5.1506 (5.8834) Loss: 5.3533 (6.1109) +2023-04-03,18:43:24 | INFO | Train Epoch: 0 [ 25664/2339328 (1%)] Data (t): 0.035 Batch (t): 0.941, 66.4000/s LR: 0.000004 Logit Scale: 99.947 Contrastive_loss: 0.038800 (0.18976) Caption_loss: 4.3085 (5.5684) Loss: 4.3473 (5.7582) +2023-04-03,18:44:59 | INFO | Train Epoch: 0 [ 32064/2339328 (1%)] Data (t): 0.035 Batch (t): 0.943, 67.6076/s LR: 0.000005 Logit Scale: 99.920 Contrastive_loss: 0.22675 (0.19592) Caption_loss: 4.8671 (5.4515) Loss: 5.0939 (5.6474) +2023-04-03,18:46:34 | INFO | Train Epoch: 0 [ 38464/2339328 (2%)] Data (t): 0.035 Batch (t): 0.953, 67.7625/s LR: 0.000006 Logit Scale: 99.886 Contrastive_loss: 0.077593 (0.17902) Caption_loss: 5.1023 (5.4016) Loss: 5.1799 (5.5807) +2023-04-03,18:48:08 | INFO | Train Epoch: 0 [ 44864/2339328 (2%)] Data (t): 0.035 Batch (t): 0.946, 68.3248/s LR: 0.000007 Logit Scale: 99.855 Contrastive_loss: 0.11941 (0.17157) Caption_loss: 4.9706 (5.3478) Loss: 5.0900 (5.5193) +2023-04-03,18:49:43 | INFO | Train Epoch: 0 [ 51264/2339328 (2%)] Data (t): 0.035 Batch (t): 0.946, 68.1814/s LR: 0.000008 Logit Scale: 99.824 Contrastive_loss: 0.26037 (0.18143) Caption_loss: 4.3950 (5.2419) Loss: 4.6554 (5.4233) +2023-04-03,18:51:18 | INFO | Train Epoch: 0 [ 57664/2339328 (2%)] Data (t): 0.035 Batch (t): 0.952, 66.2341/s LR: 0.000009 Logit Scale: 99.795 Contrastive_loss: 0.064602 (0.16975) Caption_loss: 4.4266 (5.1604) Loss: 4.4912 (5.3301) +2023-04-03,18:52:53 | INFO | Train Epoch: 0 [ 64064/2339328 (3%)] Data (t): 0.035 Batch (t): 0.946, 63.3570/s LR: 0.000010 Logit Scale: 99.753 Contrastive_loss: 0.14348 (0.16736) Caption_loss: 4.1071 (5.0646) Loss: 4.2506 (5.2320) +2023-04-03,18:54:28 | INFO | Train Epoch: 0 [ 70464/2339328 (3%)] Data (t): 0.035 Batch (t): 0.950, 67.9619/s LR: 0.000010 Logit Scale: 99.723 Contrastive_loss: 0.21525 (0.17135) Caption_loss: 5.5932 (5.1087) Loss: 5.8084 (5.2800) +2023-04-03,18:56:02 | INFO | Train Epoch: 0 [ 76864/2339328 (3%)] Data (t): 0.035 Batch (t): 0.946, 67.8243/s LR: 0.000010 Logit Scale: 99.678 Contrastive_loss: 0.020376 (0.15974) Caption_loss: 4.9931 (5.0998) Loss: 5.0134 (5.2595) +2023-04-03,18:57:37 | INFO | Train Epoch: 0 [ 83264/2339328 (4%)] Data (t): 0.035 Batch (t): 0.948, 65.8491/s LR: 0.000010 Logit Scale: 99.649 Contrastive_loss: 0.086548 (0.15451) Caption_loss: 4.8557 (5.0823) Loss: 4.9423 (5.2369) +2023-04-03,18:59:12 | INFO | Train Epoch: 0 [ 89664/2339328 (4%)] Data (t): 0.035 Batch (t): 0.948, 67.7468/s LR: 0.000010 Logit Scale: 99.628 Contrastive_loss: 0.18584 (0.15660) Caption_loss: 4.9959 (5.0766) Loss: 5.1818 (5.2332) +2023-04-03,19:00:47 | INFO | Train Epoch: 0 [ 96064/2339328 (4%)] Data (t): 0.035 Batch (t): 0.951, 68.0353/s LR: 0.000010 Logit Scale: 99.589 Contrastive_loss: 0.20925 (0.15989) Caption_loss: 5.0171 (5.0729) Loss: 5.2264 (5.2328) +2023-04-03,19:02:22 | INFO | Train Epoch: 0 [ 102464/2339328 (4%)] Data (t): 0.035 Batch (t): 0.951, 68.6839/s LR: 0.000010 Logit Scale: 99.572 Contrastive_loss: 0.092979 (0.15596) Caption_loss: 4.3532 (5.0305) Loss: 4.4461 (5.1865) +2023-04-03,19:03:57 | INFO | Train Epoch: 0 [ 108864/2339328 (5%)] Data (t): 0.035 Batch (t): 0.945, 67.2512/s LR: 0.000010 Logit Scale: 99.540 Contrastive_loss: 0.17503 (0.15701) Caption_loss: 4.1686 (4.9826) Loss: 4.3436 (5.1397) +2023-04-03,19:05:32 | INFO | Train Epoch: 0 [ 115264/2339328 (5%)] Data (t): 0.035 Batch (t): 0.953, 67.5292/s LR: 0.000010 Logit Scale: 99.524 Contrastive_loss: 0.10171 (0.15410) Caption_loss: 5.4179 (5.0055) Loss: 5.5196 (5.1597) +2023-04-03,19:07:07 | INFO | Train Epoch: 0 [ 121664/2339328 (5%)] Data (t): 0.035 Batch (t): 0.951, 67.9371/s LR: 0.000010 Logit Scale: 99.485 Contrastive_loss: 0.079065 (0.15035) Caption_loss: 5.1122 (5.0109) Loss: 5.1912 (5.1612) +2023-04-03,19:08:41 | INFO | Train Epoch: 0 [ 128064/2339328 (5%)] Data (t): 0.035 Batch (t): 0.941, 67.7519/s LR: 0.000010 Logit Scale: 99.466 Contrastive_loss: 0.11639 (0.14873) Caption_loss: 5.2146 (5.0206) Loss: 5.3310 (5.1693) +2023-04-03,19:10:16 | INFO | Train Epoch: 0 [ 134464/2339328 (6%)] Data (t): 0.035 Batch (t): 0.949, 67.7094/s LR: 0.000010 Logit Scale: 99.437 Contrastive_loss: 0.24005 (0.15289) Caption_loss: 4.8788 (5.0141) Loss: 5.1188 (5.1670) +2023-04-03,19:11:51 | INFO | Train Epoch: 0 [ 140864/2339328 (6%)] Data (t): 0.035 Batch (t): 0.952, 67.8897/s LR: 0.000010 Logit Scale: 99.420 Contrastive_loss: 0.13486 (0.15210) Caption_loss: 4.7891 (5.0044) Loss: 4.9239 (5.1565) +2023-04-03,19:13:26 | INFO | Train Epoch: 0 [ 147264/2339328 (6%)] Data (t): 0.035 Batch (t): 0.946, 66.9834/s LR: 0.000010 Logit Scale: 99.410 Contrastive_loss: 0.057576 (0.14816) Caption_loss: 4.9093 (5.0004) Loss: 4.9669 (5.1486) +2023-04-03,19:15:00 | INFO | Train Epoch: 0 [ 153664/2339328 (7%)] Data (t): 0.035 Batch (t): 0.946, 68.0789/s LR: 0.000010 Logit Scale: 99.392 Contrastive_loss: 0.082342 (0.14553) Caption_loss: 4.5995 (4.9844) Loss: 4.6818 (5.1299) +2023-04-03,19:16:35 | INFO | Train Epoch: 0 [ 160064/2339328 (7%)] Data (t): 0.035 Batch (t): 0.946, 64.9865/s LR: 0.000010 Logit Scale: 99.370 Contrastive_loss: 0.22687 (0.14866) Caption_loss: 4.6389 (4.9711) Loss: 4.8657 (5.1197) +2023-04-03,19:18:10 | INFO | Train Epoch: 0 [ 166464/2339328 (7%)] Data (t): 0.035 Batch (t): 0.945, 69.6679/s LR: 0.000010 Logit Scale: 99.354 Contrastive_loss: 0.12162 (0.14766) Caption_loss: 4.7563 (4.9631) Loss: 4.8779 (5.1108) +2023-04-03,19:19:45 | INFO | Train Epoch: 0 [ 172864/2339328 (7%)] Data (t): 0.035 Batch (t): 0.950, 68.2670/s LR: 0.000010 Logit Scale: 99.342 Contrastive_loss: 0.090342 (0.14561) Caption_loss: 5.2597 (4.9737) Loss: 5.3500 (5.1193) +2023-04-03,19:21:19 | INFO | Train Epoch: 0 [ 179264/2339328 (8%)] Data (t): 0.035 Batch (t): 0.943, 67.5942/s LR: 0.000010 Logit Scale: 99.324 Contrastive_loss: 0.29968 (0.15092) Caption_loss: 3.1680 (4.9114) Loss: 3.4676 (5.0624) +2023-04-03,19:22:55 | INFO | Train Epoch: 0 [ 185664/2339328 (8%)] Data (t): 0.035 Batch (t): 0.957, 66.9522/s LR: 0.000010 Logit Scale: 99.297 Contrastive_loss: 0.26769 (0.15481) Caption_loss: 4.1905 (4.8874) Loss: 4.4582 (5.0422) +2023-04-03,19:24:29 | INFO | Train Epoch: 0 [ 192064/2339328 (8%)] Data (t): 0.035 Batch (t): 0.945, 68.0915/s LR: 0.000010 Logit Scale: 99.288 Contrastive_loss: 0.11243 (0.15345) Caption_loss: 5.2899 (4.9004) Loss: 5.4023 (5.0538) +2023-04-03,19:26:04 | INFO | Train Epoch: 0 [ 198464/2339328 (8%)] Data (t): 0.035 Batch (t): 0.944, 68.0874/s LR: 0.000010 Logit Scale: 99.270 Contrastive_loss: 0.11672 (0.15230) Caption_loss: 4.1275 (4.8762) Loss: 4.2442 (5.0285) +2023-04-03,19:27:38 | INFO | Train Epoch: 0 [ 204864/2339328 (9%)] Data (t): 0.035 Batch (t): 0.945, 67.6771/s LR: 0.000010 Logit Scale: 99.260 Contrastive_loss: 0.10216 (0.15078) Caption_loss: 4.7206 (4.8715) Loss: 4.8227 (5.0223) +2023-04-03,19:29:12 | INFO | Train Epoch: 0 [ 211264/2339328 (9%)] Data (t): 0.035 Batch (t): 0.943, 67.8402/s LR: 0.000010 Logit Scale: 99.241 Contrastive_loss: 0.085652 (0.14887) Caption_loss: 4.3138 (4.8551) Loss: 4.3994 (5.0040) +2023-04-03,19:30:47 | INFO | Train Epoch: 0 [ 217664/2339328 (9%)] Data (t): 0.035 Batch (t): 0.947, 67.0104/s LR: 0.000010 Logit Scale: 99.214 Contrastive_loss: 0.14188 (0.14867) Caption_loss: 5.0871 (4.8617) Loss: 5.2290 (5.0104) +2023-04-03,19:32:22 | INFO | Train Epoch: 0 [ 224064/2339328 (10%)] Data (t): 0.035 Batch (t): 0.950, 69.5480/s LR: 0.000010 Logit Scale: 99.213 Contrastive_loss: 0.10706 (0.14751) Caption_loss: 4.2979 (4.8461) Loss: 4.4049 (4.9936) +2023-04-03,19:33:56 | INFO | Train Epoch: 0 [ 230464/2339328 (10%)] Data (t): 0.035 Batch (t): 0.945, 67.7820/s LR: 0.000010 Logit Scale: 99.199 Contrastive_loss: 0.41278 (0.15468) Caption_loss: 5.2454 (4.8569) Loss: 5.6582 (5.0115) +2023-04-03,19:35:31 | INFO | Train Epoch: 0 [ 236864/2339328 (10%)] Data (t): 0.035 Batch (t): 0.946, 64.9766/s LR: 0.000010 Logit Scale: 99.172 Contrastive_loss: 0.051316 (0.15196) Caption_loss: 4.0387 (4.8353) Loss: 4.0900 (4.9873) +2023-04-03,19:37:06 | INFO | Train Epoch: 0 [ 243264/2339328 (10%)] Data (t): 0.035 Batch (t): 0.947, 67.7062/s LR: 0.000010 Logit Scale: 99.166 Contrastive_loss: 0.10875 (0.15085) Caption_loss: 3.5337 (4.8020) Loss: 3.6424 (4.9528) +2023-04-03,19:38:40 | INFO | Train Epoch: 0 [ 249664/2339328 (11%)] Data (t): 0.035 Batch (t): 0.947, 68.0082/s LR: 0.000010 Logit Scale: 99.144 Contrastive_loss: 0.11685 (0.15000) Caption_loss: 4.4977 (4.7944) Loss: 4.6145 (4.9444) +2023-04-03,19:40:15 | INFO | Train Epoch: 0 [ 256064/2339328 (11%)] Data (t): 0.035 Batch (t): 0.943, 67.8782/s LR: 0.000010 Logit Scale: 99.133 Contrastive_loss: 0.26038 (0.15269) Caption_loss: 4.7558 (4.7934) Loss: 5.0162 (4.9461) +2023-04-03,19:41:50 | INFO | Train Epoch: 0 [ 262464/2339328 (11%)] Data (t): 0.035 Batch (t): 0.948, 68.2132/s LR: 0.000010 Logit Scale: 99.116 Contrastive_loss: 0.069269 (0.15071) Caption_loss: 3.5014 (4.7627) Loss: 3.5707 (4.9134) +2023-04-03,19:43:24 | INFO | Train Epoch: 0 [ 268864/2339328 (11%)] Data (t): 0.035 Batch (t): 0.948, 67.9747/s LR: 0.000010 Logit Scale: 99.097 Contrastive_loss: 0.11133 (0.14979) Caption_loss: 4.9515 (4.7670) Loss: 5.0628 (4.9168) +2023-04-03,19:44:59 | INFO | Train Epoch: 0 [ 275264/2339328 (12%)] Data (t): 0.035 Batch (t): 0.947, 67.5474/s LR: 0.000010 Logit Scale: 99.093 Contrastive_loss: 0.13149 (0.14938) Caption_loss: 5.0475 (4.7734) Loss: 5.1790 (4.9228) +2023-04-03,19:46:34 | INFO | Train Epoch: 0 [ 281664/2339328 (12%)] Data (t): 0.035 Batch (t): 0.948, 68.1821/s LR: 0.000010 Logit Scale: 99.085 Contrastive_loss: 0.18655 (0.15020) Caption_loss: 3.8178 (4.7522) Loss: 4.0043 (4.9024) +2023-04-03,19:48:09 | INFO | Train Epoch: 0 [ 288064/2339328 (12%)] Data (t): 0.035 Batch (t): 0.948, 67.6429/s LR: 0.000010 Logit Scale: 99.067 Contrastive_loss: 0.12059 (0.14956) Caption_loss: 4.2323 (4.7409) Loss: 4.3529 (4.8904) +2023-04-03,19:49:43 | INFO | Train Epoch: 0 [ 294464/2339328 (13%)] Data (t): 0.035 Batch (t): 0.944, 69.1547/s LR: 0.000010 Logit Scale: 99.050 Contrastive_loss: 0.020968 (0.14682) Caption_loss: 4.3757 (4.7331) Loss: 4.3967 (4.8799) +2023-04-03,19:51:18 | INFO | Train Epoch: 0 [ 300864/2339328 (13%)] Data (t): 0.035 Batch (t): 0.947, 66.6784/s LR: 0.000010 Logit Scale: 99.046 Contrastive_loss: 0.19536 (0.14783) Caption_loss: 4.4484 (4.7272) Loss: 4.6438 (4.8750) +2023-04-03,19:52:53 | INFO | Train Epoch: 0 [ 307264/2339328 (13%)] Data (t): 0.035 Batch (t): 0.948, 67.6170/s LR: 0.000010 Logit Scale: 99.028 Contrastive_loss: 0.013240 (0.14509) Caption_loss: 4.2178 (4.7168) Loss: 4.2310 (4.8619) +2023-04-03,19:54:27 | INFO | Train Epoch: 0 [ 313664/2339328 (13%)] Data (t): 0.035 Batch (t): 0.946, 67.5762/s LR: 0.000010 Logit Scale: 99.013 Contrastive_loss: 0.22208 (0.14663) Caption_loss: 4.3337 (4.7091) Loss: 4.5558 (4.8557) +2023-04-03,19:56:02 | INFO | Train Epoch: 0 [ 320064/2339328 (14%)] Data (t): 0.035 Batch (t): 0.947, 67.7385/s LR: 0.000010 Logit Scale: 99.012 Contrastive_loss: 0.034935 (0.14444) Caption_loss: 4.4541 (4.7041) Loss: 4.4890 (4.8486) +2023-04-03,19:57:36 | INFO | Train Epoch: 0 [ 326464/2339328 (14%)] Data (t): 0.035 Batch (t): 0.940, 68.1004/s LR: 0.000010 Logit Scale: 98.998 Contrastive_loss: 0.13113 (0.14418) Caption_loss: 5.4202 (4.7179) Loss: 5.5513 (4.8621) +2023-04-03,19:59:11 | INFO | Train Epoch: 0 [ 332864/2339328 (14%)] Data (t): 0.035 Batch (t): 0.951, 64.6542/s LR: 0.000010 Logit Scale: 98.993 Contrastive_loss: 0.15486 (0.14438) Caption_loss: 5.2992 (4.7289) Loss: 5.4541 (4.8732) +2023-04-03,20:00:46 | INFO | Train Epoch: 0 [ 339264/2339328 (15%)] Data (t): 0.035 Batch (t): 0.945, 66.2233/s LR: 0.000010 Logit Scale: 98.982 Contrastive_loss: 0.057448 (0.14277) Caption_loss: 4.3657 (4.7221) Loss: 4.4232 (4.8649) +2023-04-03,20:02:20 | INFO | Train Epoch: 0 [ 345664/2339328 (15%)] Data (t): 0.035 Batch (t): 0.949, 67.7883/s LR: 0.000010 Logit Scale: 98.964 Contrastive_loss: 0.045275 (0.14100) Caption_loss: 5.4857 (4.7360) Loss: 5.5310 (4.8770) +2023-04-03,20:03:55 | INFO | Train Epoch: 0 [ 352064/2339328 (15%)] Data (t): 0.035 Batch (t): 0.942, 67.8588/s LR: 0.000010 Logit Scale: 98.958 Contrastive_loss: 0.11464 (0.14053) Caption_loss: 4.2021 (4.7265) Loss: 4.3168 (4.8670) +2023-04-03,20:05:29 | INFO | Train Epoch: 0 [ 358464/2339328 (15%)] Data (t): 0.035 Batch (t): 0.948, 68.3132/s LR: 0.000010 Logit Scale: 98.956 Contrastive_loss: 0.22884 (0.14208) Caption_loss: 4.2712 (4.7185) Loss: 4.5001 (4.8606) +2023-04-03,20:07:04 | INFO | Train Epoch: 0 [ 364864/2339328 (16%)] Data (t): 0.035 Batch (t): 0.944, 69.2646/s LR: 0.000010 Logit Scale: 98.945 Contrastive_loss: 0.34438 (0.14557) Caption_loss: 5.0590 (4.7244) Loss: 5.4033 (4.8699) +2023-04-03,20:08:38 | INFO | Train Epoch: 0 [ 371264/2339328 (16%)] Data (t): 0.035 Batch (t): 0.947, 64.7527/s LR: 0.000010 Logit Scale: 98.936 Contrastive_loss: 0.089629 (0.14462) Caption_loss: 5.7505 (4.7418) Loss: 5.8401 (4.8864) +2023-04-03,20:10:13 | INFO | Train Epoch: 0 [ 377664/2339328 (16%)] Data (t): 0.035 Batch (t): 0.947, 68.2316/s LR: 0.000010 Logit Scale: 98.920 Contrastive_loss: 0.086559 (0.14365) Caption_loss: 4.4642 (4.7371) Loss: 4.5508 (4.8808) +2023-04-03,20:11:48 | INFO | Train Epoch: 0 [ 384064/2339328 (16%)] Data (t): 0.035 Batch (t): 0.949, 68.1186/s LR: 0.000010 Logit Scale: 98.913 Contrastive_loss: 0.065726 (0.14237) Caption_loss: 4.9648 (4.7409) Loss: 5.0305 (4.8832) +2023-04-03,20:13:22 | INFO | Train Epoch: 0 [ 390464/2339328 (17%)] Data (t): 0.035 Batch (t): 0.943, 67.0626/s LR: 0.000010 Logit Scale: 98.903 Contrastive_loss: 0.20721 (0.14342) Caption_loss: 4.7131 (4.7404) Loss: 4.9203 (4.8838) +2023-04-03,20:14:57 | INFO | Train Epoch: 0 [ 396864/2339328 (17%)] Data (t): 0.035 Batch (t): 0.950, 69.0347/s LR: 0.000009 Logit Scale: 98.884 Contrastive_loss: 0.067859 (0.14222) Caption_loss: 5.2145 (4.7479) Loss: 5.2824 (4.8902) +2023-04-03,20:16:32 | INFO | Train Epoch: 0 [ 403264/2339328 (17%)] Data (t): 0.035 Batch (t): 0.951, 67.6802/s LR: 0.000009 Logit Scale: 98.886 Contrastive_loss: 0.092784 (0.14145) Caption_loss: 5.2382 (4.7556) Loss: 5.3309 (4.8971) +2023-04-03,20:18:08 | INFO | Train Epoch: 0 [ 409664/2339328 (18%)] Data (t): 0.035 Batch (t): 0.951, 67.6179/s LR: 0.000009 Logit Scale: 98.870 Contrastive_loss: 0.16361 (0.14179) Caption_loss: 5.3041 (4.7640) Loss: 5.4677 (4.9058) +2023-04-03,20:19:42 | INFO | Train Epoch: 0 [ 416064/2339328 (18%)] Data (t): 0.035 Batch (t): 0.946, 67.2823/s LR: 0.000009 Logit Scale: 98.856 Contrastive_loss: 0.069770 (0.14070) Caption_loss: 4.9761 (4.7673) Loss: 5.0459 (4.9080) +2023-04-03,20:21:17 | INFO | Train Epoch: 0 [ 422464/2339328 (18%)] Data (t): 0.035 Batch (t): 0.951, 67.0672/s LR: 0.000009 Logit Scale: 98.843 Contrastive_loss: 0.25144 (0.14235) Caption_loss: 3.9493 (4.7550) Loss: 4.2008 (4.8974) +2023-04-03,20:22:53 | INFO | Train Epoch: 0 [ 428864/2339328 (18%)] Data (t): 0.035 Batch (t): 0.954, 67.9643/s LR: 0.000009 Logit Scale: 98.826 Contrastive_loss: 0.19725 (0.14316) Caption_loss: 5.2897 (4.7629) Loss: 5.4870 (4.9061) +2023-04-03,20:24:27 | INFO | Train Epoch: 0 [ 435264/2339328 (19%)] Data (t): 0.035 Batch (t): 0.944, 67.9692/s LR: 0.000009 Logit Scale: 98.819 Contrastive_loss: 0.13231 (0.14300) Caption_loss: 5.2434 (4.7699) Loss: 5.3757 (4.9129) +2023-04-03,20:26:01 | INFO | Train Epoch: 0 [ 441664/2339328 (19%)] Data (t): 0.035 Batch (t): 0.944, 68.5909/s LR: 0.000009 Logit Scale: 98.803 Contrastive_loss: 0.11304 (0.14257) Caption_loss: 4.9849 (4.7729) Loss: 5.0979 (4.9155) +2023-04-03,20:27:36 | INFO | Train Epoch: 0 [ 448064/2339328 (19%)] Data (t): 0.035 Batch (t): 0.947, 67.2749/s LR: 0.000009 Logit Scale: 98.788 Contrastive_loss: 0.15878 (0.14280) Caption_loss: 4.3852 (4.7675) Loss: 4.5440 (4.9103) +2023-04-03,20:29:10 | INFO | Train Epoch: 0 [ 454464/2339328 (19%)] Data (t): 0.035 Batch (t): 0.942, 69.3373/s LR: 0.000009 Logit Scale: 98.787 Contrastive_loss: 0.067202 (0.14175) Caption_loss: 4.9981 (4.7707) Loss: 5.0653 (4.9124) +2023-04-03,20:30:45 | INFO | Train Epoch: 0 [ 460864/2339328 (20%)] Data (t): 0.035 Batch (t): 0.947, 67.4129/s LR: 0.000009 Logit Scale: 98.790 Contrastive_loss: 0.11925 (0.14144) Caption_loss: 4.0893 (4.7614) Loss: 4.2086 (4.9028) +2023-04-03,20:32:20 | INFO | Train Epoch: 0 [ 467264/2339328 (20%)] Data (t): 0.035 Batch (t): 0.949, 67.6317/s LR: 0.000009 Logit Scale: 98.775 Contrastive_loss: 0.10925 (0.14101) Caption_loss: 5.0801 (4.7657) Loss: 5.1894 (4.9067) +2023-04-03,20:33:56 | INFO | Train Epoch: 0 [ 473664/2339328 (20%)] Data (t): 0.035 Batch (t): 0.955, 65.2905/s LR: 0.000009 Logit Scale: 98.763 Contrastive_loss: 0.11094 (0.14061) Caption_loss: 3.9187 (4.7544) Loss: 4.0296 (4.8950) +2023-04-03,20:35:31 | INFO | Train Epoch: 0 [ 480064/2339328 (21%)] Data (t): 0.035 Batch (t): 0.954, 63.8295/s LR: 0.000009 Logit Scale: 98.753 Contrastive_loss: 0.28950 (0.14256) Caption_loss: 4.7467 (4.7543) Loss: 5.0362 (4.8968) +2023-04-03,20:37:06 | INFO | Train Epoch: 0 [ 486464/2339328 (21%)] Data (t): 0.035 Batch (t): 0.948, 67.2209/s LR: 0.000009 Logit Scale: 98.747 Contrastive_loss: 0.15019 (0.14266) Caption_loss: 3.5530 (4.7387) Loss: 3.7032 (4.8813) +2023-04-03,20:38:40 | INFO | Train Epoch: 0 [ 492864/2339328 (21%)] Data (t): 0.035 Batch (t): 0.946, 68.0361/s LR: 0.000009 Logit Scale: 98.733 Contrastive_loss: 0.10926 (0.14224) Caption_loss: 3.9768 (4.7289) Loss: 4.0861 (4.8711) +2023-04-03,20:40:16 | INFO | Train Epoch: 0 [ 499264/2339328 (21%)] Data (t): 0.035 Batch (t): 0.955, 63.6934/s LR: 0.000009 Logit Scale: 98.714 Contrastive_loss: 0.026684 (0.14077) Caption_loss: 4.6771 (4.7282) Loss: 4.7038 (4.8690) +2023-04-03,20:41:50 | INFO | Train Epoch: 0 [ 505664/2339328 (22%)] Data (t): 0.035 Batch (t): 0.944, 68.3217/s LR: 0.000009 Logit Scale: 98.691 Contrastive_loss: 0.011247 (0.13915) Caption_loss: 4.4491 (4.7248) Loss: 4.4604 (4.8639) +2023-04-03,20:43:26 | INFO | Train Epoch: 0 [ 512064/2339328 (22%)] Data (t): 0.035 Batch (t): 0.956, 68.0758/s LR: 0.000009 Logit Scale: 98.685 Contrastive_loss: 0.13409 (0.13909) Caption_loss: 4.3413 (4.7200) Loss: 4.4754 (4.8591) +2023-04-03,20:45:00 | INFO | Train Epoch: 0 [ 518464/2339328 (22%)] Data (t): 0.035 Batch (t): 0.946, 67.2744/s LR: 0.000009 Logit Scale: 98.685 Contrastive_loss: 0.039415 (0.13788) Caption_loss: 4.8776 (4.7219) Loss: 4.9170 (4.8598) +2023-04-03,20:46:35 | INFO | Train Epoch: 0 [ 524864/2339328 (22%)] Data (t): 0.035 Batch (t): 0.948, 68.1006/s LR: 0.000009 Logit Scale: 98.684 Contrastive_loss: 0.098183 (0.13740) Caption_loss: 4.0647 (4.7140) Loss: 4.1628 (4.8514) +2023-04-03,20:48:10 | INFO | Train Epoch: 0 [ 531264/2339328 (23%)] Data (t): 0.035 Batch (t): 0.949, 68.3804/s LR: 0.000009 Logit Scale: 98.680 Contrastive_loss: 0.17631 (0.13786) Caption_loss: 5.5117 (4.7235) Loss: 5.6880 (4.8614) +2023-04-03,20:49:45 | INFO | Train Epoch: 0 [ 537664/2339328 (23%)] Data (t): 0.035 Batch (t): 0.949, 68.9701/s LR: 0.000009 Logit Scale: 98.672 Contrastive_loss: 0.13944 (0.13788) Caption_loss: 4.3467 (4.7191) Loss: 4.4862 (4.8570) +2023-04-03,20:51:20 | INFO | Train Epoch: 0 [ 544064/2339328 (23%)] Data (t): 0.035 Batch (t): 0.953, 64.9440/s LR: 0.000009 Logit Scale: 98.657 Contrastive_loss: 0.12893 (0.13777) Caption_loss: 5.4115 (4.7271) Loss: 5.5405 (4.8649) +2023-04-03,20:52:55 | INFO | Train Epoch: 0 [ 550464/2339328 (24%)] Data (t): 0.035 Batch (t): 0.948, 68.3157/s LR: 0.000009 Logit Scale: 98.650 Contrastive_loss: 0.13960 (0.13780) Caption_loss: 4.6582 (4.7263) Loss: 4.7978 (4.8641) +2023-04-03,20:54:31 | INFO | Train Epoch: 0 [ 556864/2339328 (24%)] Data (t): 0.035 Batch (t): 0.960, 65.2859/s LR: 0.000009 Logit Scale: 98.638 Contrastive_loss: 0.23191 (0.13887) Caption_loss: 4.9706 (4.7291) Loss: 5.2025 (4.8680) +2023-04-03,20:56:06 | INFO | Train Epoch: 0 [ 563264/2339328 (24%)] Data (t): 0.035 Batch (t): 0.946, 66.2396/s LR: 0.000009 Logit Scale: 98.628 Contrastive_loss: 0.089850 (0.13831) Caption_loss: 3.9562 (4.7204) Loss: 4.0461 (4.8588) +2023-04-03,20:57:40 | INFO | Train Epoch: 0 [ 569664/2339328 (24%)] Data (t): 0.035 Batch (t): 0.947, 68.1583/s LR: 0.000009 Logit Scale: 98.619 Contrastive_loss: 0.079529 (0.13766) Caption_loss: 5.5711 (4.7299) Loss: 5.6506 (4.8675) +2023-04-03,20:59:15 | INFO | Train Epoch: 0 [ 576064/2339328 (25%)] Data (t): 0.035 Batch (t): 0.945, 68.0109/s LR: 0.000009 Logit Scale: 98.602 Contrastive_loss: 0.13102 (0.13759) Caption_loss: 5.0681 (4.7336) Loss: 5.1992 (4.8712) +2023-04-03,21:00:50 | INFO | Train Epoch: 0 [ 582464/2339328 (25%)] Data (t): 0.035 Batch (t): 0.947, 69.5728/s LR: 0.000009 Logit Scale: 98.597 Contrastive_loss: 0.13810 (0.13759) Caption_loss: 4.2437 (4.7283) Loss: 4.3818 (4.8659) +2023-04-03,21:02:24 | INFO | Train Epoch: 0 [ 588864/2339328 (25%)] Data (t): 0.035 Batch (t): 0.948, 68.4184/s LR: 0.000009 Logit Scale: 98.582 Contrastive_loss: 0.16524 (0.13789) Caption_loss: 5.2420 (4.7338) Loss: 5.4072 (4.8717) +2023-04-03,21:03:59 | INFO | Train Epoch: 0 [ 595264/2339328 (25%)] Data (t): 0.035 Batch (t): 0.949, 68.2825/s LR: 0.000009 Logit Scale: 98.570 Contrastive_loss: 0.17444 (0.13828) Caption_loss: 4.4127 (4.7304) Loss: 4.5872 (4.8687) +2023-04-03,21:05:34 | INFO | Train Epoch: 0 [ 601664/2339328 (26%)] Data (t): 0.035 Batch (t): 0.950, 67.2373/s LR: 0.000009 Logit Scale: 98.569 Contrastive_loss: 0.11848 (0.13807) Caption_loss: 4.7412 (4.7305) Loss: 4.8596 (4.8686) +2023-04-03,21:07:09 | INFO | Train Epoch: 0 [ 608064/2339328 (26%)] Data (t): 0.035 Batch (t): 0.948, 65.3082/s LR: 0.000009 Logit Scale: 98.566 Contrastive_loss: 0.060459 (0.13726) Caption_loss: 3.9758 (4.7226) Loss: 4.0362 (4.8599) +2023-04-03,21:08:44 | INFO | Train Epoch: 0 [ 614464/2339328 (26%)] Data (t): 0.035 Batch (t): 0.945, 69.4307/s LR: 0.000009 Logit Scale: 98.562 Contrastive_loss: 0.11589 (0.13704) Caption_loss: 4.6102 (4.7215) Loss: 4.7261 (4.8585) +2023-04-03,21:10:19 | INFO | Train Epoch: 0 [ 620864/2339328 (27%)] Data (t): 0.035 Batch (t): 0.953, 68.4457/s LR: 0.000009 Logit Scale: 98.548 Contrastive_loss: 0.16726 (0.13735) Caption_loss: 4.4633 (4.7188) Loss: 4.6305 (4.8562) +2023-04-03,21:11:53 | INFO | Train Epoch: 0 [ 627264/2339328 (27%)] Data (t): 0.036 Batch (t): 0.944, 68.4654/s LR: 0.000009 Logit Scale: 98.546 Contrastive_loss: 0.035503 (0.13632) Caption_loss: 4.9728 (4.7214) Loss: 5.0083 (4.8577) +2023-04-03,21:13:28 | INFO | Train Epoch: 0 [ 633664/2339328 (27%)] Data (t): 0.035 Batch (t): 0.951, 66.7390/s LR: 0.000009 Logit Scale: 98.533 Contrastive_loss: 0.069130 (0.13565) Caption_loss: 4.6991 (4.7212) Loss: 4.7682 (4.8568) +2023-04-03,21:15:03 | INFO | Train Epoch: 0 [ 640064/2339328 (27%)] Data (t): 0.035 Batch (t): 0.947, 68.1916/s LR: 0.000009 Logit Scale: 98.530 Contrastive_loss: 0.098955 (0.13529) Caption_loss: 6.0925 (4.7348) Loss: 6.1915 (4.8701) +2023-04-03,21:16:38 | INFO | Train Epoch: 0 [ 646464/2339328 (28%)] Data (t): 0.035 Batch (t): 0.948, 68.6079/s LR: 0.000008 Logit Scale: 98.527 Contrastive_loss: 0.094916 (0.13489) Caption_loss: 4.2471 (4.7300) Loss: 4.3420 (4.8649) +2023-04-03,21:18:13 | INFO | Train Epoch: 0 [ 652864/2339328 (28%)] Data (t): 0.035 Batch (t): 0.946, 64.6678/s LR: 0.000008 Logit Scale: 98.517 Contrastive_loss: 0.13567 (0.13490) Caption_loss: 4.3251 (4.7261) Loss: 4.4608 (4.8610) +2023-04-03,21:19:47 | INFO | Train Epoch: 0 [ 659264/2339328 (28%)] Data (t): 0.035 Batch (t): 0.945, 67.8066/s LR: 0.000008 Logit Scale: 98.509 Contrastive_loss: 0.079912 (0.13437) Caption_loss: 5.5095 (4.7336) Loss: 5.5894 (4.8680) +2023-04-03,21:21:22 | INFO | Train Epoch: 0 [ 665664/2339328 (28%)] Data (t): 0.035 Batch (t): 0.945, 67.4705/s LR: 0.000008 Logit Scale: 98.499 Contrastive_loss: 0.14710 (0.13449) Caption_loss: 5.4406 (4.7403) Loss: 5.5877 (4.8748) +2023-04-03,21:22:56 | INFO | Train Epoch: 0 [ 672064/2339328 (29%)] Data (t): 0.035 Batch (t): 0.946, 66.6334/s LR: 0.000008 Logit Scale: 98.501 Contrastive_loss: 0.10621 (0.13422) Caption_loss: 4.5718 (4.7387) Loss: 4.6781 (4.8730) +2023-04-03,21:24:31 | INFO | Train Epoch: 0 [ 678464/2339328 (29%)] Data (t): 0.035 Batch (t): 0.946, 64.2452/s LR: 0.000008 Logit Scale: 98.490 Contrastive_loss: 0.090205 (0.13381) Caption_loss: 5.2257 (4.7433) Loss: 5.3159 (4.8771) +2023-04-03,21:26:05 | INFO | Train Epoch: 0 [ 684864/2339328 (29%)] Data (t): 0.035 Batch (t): 0.947, 68.7589/s LR: 0.000008 Logit Scale: 98.479 Contrastive_loss: 0.17246 (0.13417) Caption_loss: 4.2382 (4.7386) Loss: 4.4107 (4.8728) +2023-04-03,21:27:40 | INFO | Train Epoch: 0 [ 691264/2339328 (30%)] Data (t): 0.035 Batch (t): 0.942, 66.7911/s LR: 0.000008 Logit Scale: 98.466 Contrastive_loss: 0.20315 (0.13480) Caption_loss: 4.4793 (4.7362) Loss: 4.6824 (4.8710) +2023-04-03,21:29:14 | INFO | Train Epoch: 0 [ 697664/2339328 (30%)] Data (t): 0.035 Batch (t): 0.940, 67.0603/s LR: 0.000008 Logit Scale: 98.461 Contrastive_loss: 0.14015 (0.13485) Caption_loss: 5.1224 (4.7397) Loss: 5.2625 (4.8746) +2023-04-03,21:30:48 | INFO | Train Epoch: 0 [ 704064/2339328 (30%)] Data (t): 0.035 Batch (t): 0.939, 66.3822/s LR: 0.000008 Logit Scale: 98.455 Contrastive_loss: 0.067284 (0.13424) Caption_loss: 4.4221 (4.7369) Loss: 4.4894 (4.8711) +2023-04-03,21:32:22 | INFO | Train Epoch: 0 [ 710464/2339328 (30%)] Data (t): 0.035 Batch (t): 0.944, 68.5516/s LR: 0.000008 Logit Scale: 98.443 Contrastive_loss: 0.083674 (0.13379) Caption_loss: 4.5667 (4.7354) Loss: 4.6504 (4.8691) +2023-04-03,21:33:57 | INFO | Train Epoch: 0 [ 716864/2339328 (31%)] Data (t): 0.035 Batch (t): 0.946, 68.7013/s LR: 0.000008 Logit Scale: 98.439 Contrastive_loss: 0.086438 (0.13337) Caption_loss: 4.1512 (4.7302) Loss: 4.2377 (4.8636) +2023-04-03,21:35:31 | INFO | Train Epoch: 0 [ 723264/2339328 (31%)] Data (t): 0.035 Batch (t): 0.941, 68.7698/s LR: 0.000008 Logit Scale: 98.429 Contrastive_loss: 0.13473 (0.13338) Caption_loss: 5.0534 (4.7330) Loss: 5.1881 (4.8664) +2023-04-03,21:37:04 | INFO | Train Epoch: 0 [ 729664/2339328 (31%)] Data (t): 0.035 Batch (t): 0.938, 69.2542/s LR: 0.000008 Logit Scale: 98.413 Contrastive_loss: 0.15087 (0.13354) Caption_loss: 5.6134 (4.7407) Loss: 5.7643 (4.8742) +2023-04-03,21:38:38 | INFO | Train Epoch: 0 [ 736064/2339328 (31%)] Data (t): 0.035 Batch (t): 0.939, 70.0193/s LR: 0.000008 Logit Scale: 98.412 Contrastive_loss: 0.17645 (0.13391) Caption_loss: 4.7967 (4.7412) Loss: 4.9731 (4.8751) +2023-04-03,21:40:12 | INFO | Train Epoch: 0 [ 742464/2339328 (32%)] Data (t): 0.035 Batch (t): 0.942, 69.6058/s LR: 0.000008 Logit Scale: 98.396 Contrastive_loss: 0.055655 (0.13324) Caption_loss: 5.2993 (4.7459) Loss: 5.3549 (4.8792) +2023-04-03,21:41:47 | INFO | Train Epoch: 0 [ 748864/2339328 (32%)] Data (t): 0.035 Batch (t): 0.943, 67.1206/s LR: 0.000008 Logit Scale: 98.395 Contrastive_loss: 0.12811 (0.13319) Caption_loss: 5.1477 (4.7493) Loss: 5.2758 (4.8825) +2023-04-03,21:43:21 | INFO | Train Epoch: 0 [ 755264/2339328 (32%)] Data (t): 0.035 Batch (t): 0.940, 67.5185/s LR: 0.000008 Logit Scale: 98.394 Contrastive_loss: 0.13726 (0.13323) Caption_loss: 5.0338 (4.7517) Loss: 5.1711 (4.8850) +2023-04-03,21:44:55 | INFO | Train Epoch: 0 [ 761664/2339328 (33%)] Data (t): 0.035 Batch (t): 0.943, 69.0536/s LR: 0.000008 Logit Scale: 98.393 Contrastive_loss: 0.14884 (0.13336) Caption_loss: 5.7672 (4.7602) Loss: 5.9161 (4.8935) +2023-04-03,21:46:29 | INFO | Train Epoch: 0 [ 768064/2339328 (33%)] Data (t): 0.035 Batch (t): 0.943, 69.4941/s LR: 0.000008 Logit Scale: 98.384 Contrastive_loss: 0.076360 (0.13289) Caption_loss: 3.7385 (4.7517) Loss: 3.8148 (4.8846) +2023-04-03,21:48:04 | INFO | Train Epoch: 0 [ 774464/2339328 (33%)] Data (t): 0.035 Batch (t): 0.942, 68.0044/s LR: 0.000008 Logit Scale: 98.378 Contrastive_loss: 0.060064 (0.13229) Caption_loss: 4.6428 (4.7509) Loss: 4.7029 (4.8831) +2023-04-03,21:49:38 | INFO | Train Epoch: 0 [ 780864/2339328 (33%)] Data (t): 0.035 Batch (t): 0.942, 66.3113/s LR: 0.000008 Logit Scale: 98.382 Contrastive_loss: 0.21641 (0.13297) Caption_loss: 3.6602 (4.7420) Loss: 3.8767 (4.8750) +2023-04-03,21:51:12 | INFO | Train Epoch: 0 [ 787264/2339328 (34%)] Data (t): 0.035 Batch (t): 0.942, 68.5448/s LR: 0.000008 Logit Scale: 98.375 Contrastive_loss: 0.082672 (0.13257) Caption_loss: 4.3276 (4.7386) Loss: 4.4102 (4.8712) +2023-04-03,21:52:46 | INFO | Train Epoch: 0 [ 793664/2339328 (34%)] Data (t): 0.035 Batch (t): 0.941, 67.3726/s LR: 0.000008 Logit Scale: 98.367 Contrastive_loss: 0.084499 (0.13218) Caption_loss: 5.2989 (4.7431) Loss: 5.3834 (4.8753) +2023-04-03,21:54:20 | INFO | Train Epoch: 0 [ 800064/2339328 (34%)] Data (t): 0.036 Batch (t): 0.940, 67.4986/s LR: 0.000008 Logit Scale: 98.370 Contrastive_loss: 0.18026 (0.13257) Caption_loss: 4.4873 (4.7411) Loss: 4.6676 (4.8737) +2023-04-03,21:55:54 | INFO | Train Epoch: 0 [ 806464/2339328 (34%)] Data (t): 0.035 Batch (t): 0.941, 68.7852/s LR: 0.000008 Logit Scale: 98.358 Contrastive_loss: 0.13539 (0.13259) Caption_loss: 3.3288 (4.7300) Loss: 3.4642 (4.8626) +2023-04-03,21:57:28 | INFO | Train Epoch: 0 [ 812864/2339328 (35%)] Data (t): 0.035 Batch (t): 0.941, 69.7288/s LR: 0.000008 Logit Scale: 98.363 Contrastive_loss: 0.12373 (0.13252) Caption_loss: 4.7269 (4.7300) Loss: 4.8507 (4.8625) +2023-04-03,21:59:02 | INFO | Train Epoch: 0 [ 819264/2339328 (35%)] Data (t): 0.035 Batch (t): 0.941, 67.6977/s LR: 0.000008 Logit Scale: 98.359 Contrastive_loss: 0.081255 (0.13212) Caption_loss: 5.6021 (4.7367) Loss: 5.6833 (4.8688) +2023-04-03,22:00:36 | INFO | Train Epoch: 0 [ 825664/2339328 (35%)] Data (t): 0.035 Batch (t): 0.938, 68.7019/s LR: 0.000007 Logit Scale: 98.341 Contrastive_loss: 0.17909 (0.13248) Caption_loss: 4.3370 (4.7336) Loss: 4.5161 (4.8661) +2023-04-03,22:02:10 | INFO | Train Epoch: 0 [ 832064/2339328 (36%)] Data (t): 0.036 Batch (t): 0.940, 67.7370/s LR: 0.000007 Logit Scale: 98.332 Contrastive_loss: 0.070180 (0.13201) Caption_loss: 4.8624 (4.7346) Loss: 4.9326 (4.8666) +2023-04-03,22:03:44 | INFO | Train Epoch: 0 [ 838464/2339328 (36%)] Data (t): 0.035 Batch (t): 0.942, 67.3485/s LR: 0.000007 Logit Scale: 98.328 Contrastive_loss: 0.12806 (0.13198) Caption_loss: 3.3845 (4.7244) Loss: 3.5126 (4.8564) +2023-04-03,22:05:19 | INFO | Train Epoch: 0 [ 844864/2339328 (36%)] Data (t): 0.035 Batch (t): 0.941, 67.3848/s LR: 0.000007 Logit Scale: 98.324 Contrastive_loss: 0.20517 (0.13253) Caption_loss: 3.8342 (4.7177) Loss: 4.0394 (4.8502) +2023-04-03,22:06:53 | INFO | Train Epoch: 0 [ 851264/2339328 (36%)] Data (t): 0.035 Batch (t): 0.942, 68.2986/s LR: 0.000007 Logit Scale: 98.319 Contrastive_loss: 0.13477 (0.13254) Caption_loss: 3.9307 (4.7118) Loss: 4.0655 (4.8444) +2023-04-03,22:08:27 | INFO | Train Epoch: 0 [ 857664/2339328 (37%)] Data (t): 0.035 Batch (t): 0.939, 66.2091/s LR: 0.000007 Logit Scale: 98.310 Contrastive_loss: 0.096914 (0.13228) Caption_loss: 4.3536 (4.7092) Loss: 4.4506 (4.8415) +2023-04-03,22:10:01 | INFO | Train Epoch: 0 [ 864064/2339328 (37%)] Data (t): 0.035 Batch (t): 0.941, 65.2261/s LR: 0.000007 Logit Scale: 98.311 Contrastive_loss: 0.12791 (0.13225) Caption_loss: 4.0237 (4.7041) Loss: 4.1517 (4.8364) +2023-04-03,22:11:35 | INFO | Train Epoch: 0 [ 870464/2339328 (37%)] Data (t): 0.035 Batch (t): 0.946, 69.0208/s LR: 0.000007 Logit Scale: 98.313 Contrastive_loss: 0.21891 (0.13288) Caption_loss: 3.8939 (4.6982) Loss: 4.1128 (4.8311) +2023-04-03,22:13:09 | INFO | Train Epoch: 0 [ 876864/2339328 (37%)] Data (t): 0.035 Batch (t): 0.942, 67.2062/s LR: 0.000007 Logit Scale: 98.304 Contrastive_loss: 0.11399 (0.13274) Caption_loss: 4.7389 (4.6985) Loss: 4.8529 (4.8313) +2023-04-03,22:14:44 | INFO | Train Epoch: 0 [ 883264/2339328 (38%)] Data (t): 0.035 Batch (t): 0.945, 68.5200/s LR: 0.000007 Logit Scale: 98.295 Contrastive_loss: 0.069802 (0.13229) Caption_loss: 4.8111 (4.6993) Loss: 4.8809 (4.8316) +2023-04-03,22:16:18 | INFO | Train Epoch: 0 [ 889664/2339328 (38%)] Data (t): 0.035 Batch (t): 0.937, 68.0032/s LR: 0.000007 Logit Scale: 98.292 Contrastive_loss: 0.053102 (0.13173) Caption_loss: 4.1195 (4.6952) Loss: 4.1726 (4.8269) +2023-04-03,22:17:51 | INFO | Train Epoch: 0 [ 896064/2339328 (38%)] Data (t): 0.035 Batch (t): 0.938, 68.4661/s LR: 0.000007 Logit Scale: 98.290 Contrastive_loss: 0.31995 (0.13306) Caption_loss: 4.9166 (4.6968) Loss: 5.2365 (4.8298) +2023-04-03,22:19:26 | INFO | Train Epoch: 0 [ 902464/2339328 (39%)] Data (t): 0.035 Batch (t): 0.945, 67.2094/s LR: 0.000007 Logit Scale: 98.282 Contrastive_loss: 0.087175 (0.13274) Caption_loss: 4.8885 (4.6981) Loss: 4.9757 (4.8308) +2023-04-03,22:21:00 | INFO | Train Epoch: 0 [ 908864/2339328 (39%)] Data (t): 0.035 Batch (t): 0.942, 63.9901/s LR: 0.000007 Logit Scale: 98.273 Contrastive_loss: 0.10612 (0.13255) Caption_loss: 4.5364 (4.6970) Loss: 4.6425 (4.8295) +2023-04-03,22:22:35 | INFO | Train Epoch: 0 [ 915264/2339328 (39%)] Data (t): 0.035 Batch (t): 0.944, 68.8911/s LR: 0.000007 Logit Scale: 98.278 Contrastive_loss: 0.027969 (0.13183) Caption_loss: 5.2343 (4.7007) Loss: 5.2623 (4.8325) +2023-04-03,22:24:08 | INFO | Train Epoch: 0 [ 921664/2339328 (39%)] Data (t): 0.035 Batch (t): 0.939, 68.4426/s LR: 0.000007 Logit Scale: 98.274 Contrastive_loss: 0.085681 (0.13151) Caption_loss: 5.4041 (4.7056) Loss: 5.4898 (4.8371) +2023-04-03,22:25:43 | INFO | Train Epoch: 0 [ 928064/2339328 (40%)] Data (t): 0.035 Batch (t): 0.943, 67.7847/s LR: 0.000007 Logit Scale: 98.269 Contrastive_loss: 0.12835 (0.13149) Caption_loss: 4.2964 (4.7028) Loss: 4.4248 (4.8342) +2023-04-03,22:27:17 | INFO | Train Epoch: 0 [ 934464/2339328 (40%)] Data (t): 0.035 Batch (t): 0.941, 69.0038/s LR: 0.000007 Logit Scale: 98.266 Contrastive_loss: 0.059861 (0.13100) Caption_loss: 4.0410 (4.6982) Loss: 4.1009 (4.8292) +2023-04-03,22:28:51 | INFO | Train Epoch: 0 [ 940864/2339328 (40%)] Data (t): 0.035 Batch (t): 0.939, 67.5386/s LR: 0.000007 Logit Scale: 98.277 Contrastive_loss: 0.10325 (0.13081) Caption_loss: 3.2301 (4.6883) Loss: 3.3334 (4.8191) +2023-04-03,22:30:25 | INFO | Train Epoch: 0 [ 947264/2339328 (40%)] Data (t): 0.035 Batch (t): 0.941, 64.8612/s LR: 0.000007 Logit Scale: 98.274 Contrastive_loss: 0.071101 (0.13041) Caption_loss: 3.0963 (4.6776) Loss: 3.1674 (4.8081) +2023-04-03,22:31:59 | INFO | Train Epoch: 0 [ 953664/2339328 (41%)] Data (t): 0.035 Batch (t): 0.944, 68.9012/s LR: 0.000007 Logit Scale: 98.268 Contrastive_loss: 0.077845 (0.13006) Caption_loss: 4.3623 (4.6755) Loss: 4.4402 (4.8056) +2023-04-03,22:33:34 | INFO | Train Epoch: 0 [ 960064/2339328 (41%)] Data (t): 0.035 Batch (t): 0.946, 66.3199/s LR: 0.000007 Logit Scale: 98.265 Contrastive_loss: 0.096303 (0.12984) Caption_loss: 4.1425 (4.6720) Loss: 4.2388 (4.8018) +2023-04-03,22:35:08 | INFO | Train Epoch: 0 [ 966464/2339328 (41%)] Data (t): 0.035 Batch (t): 0.940, 68.1504/s LR: 0.000007 Logit Scale: 98.252 Contrastive_loss: 0.24794 (0.13061) Caption_loss: 5.2008 (4.6755) Loss: 5.4488 (4.8061) +2023-04-03,22:36:42 | INFO | Train Epoch: 0 [ 972864/2339328 (42%)] Data (t): 0.035 Batch (t): 0.939, 68.4589/s LR: 0.000007 Logit Scale: 98.249 Contrastive_loss: 0.082551 (0.13030) Caption_loss: 5.1179 (4.6784) Loss: 5.2005 (4.8087) +2023-04-03,22:38:16 | INFO | Train Epoch: 0 [ 979264/2339328 (42%)] Data (t): 0.035 Batch (t): 0.940, 69.4955/s LR: 0.000007 Logit Scale: 98.240 Contrastive_loss: 0.10701 (0.13015) Caption_loss: 5.1298 (4.6813) Loss: 5.2369 (4.8115) +2023-04-03,22:39:50 | INFO | Train Epoch: 0 [ 985664/2339328 (42%)] Data (t): 0.035 Batch (t): 0.940, 68.7538/s LR: 0.000006 Logit Scale: 98.232 Contrastive_loss: 0.14995 (0.13028) Caption_loss: 3.2773 (4.6723) Loss: 3.4272 (4.8025) +2023-04-03,22:41:24 | INFO | Train Epoch: 0 [ 992064/2339328 (42%)] Data (t): 0.036 Batch (t): 0.944, 68.2833/s LR: 0.000006 Logit Scale: 98.228 Contrastive_loss: 0.10920 (0.13014) Caption_loss: 4.3310 (4.6701) Loss: 4.4402 (4.8002) +2023-04-03,22:42:58 | INFO | Train Epoch: 0 [ 998464/2339328 (43%)] Data (t): 0.036 Batch (t): 0.943, 69.2647/s LR: 0.000006 Logit Scale: 98.227 Contrastive_loss: 0.054608 (0.12966) Caption_loss: 3.4824 (4.6625) Loss: 3.5370 (4.7922) +2023-04-03,22:44:33 | INFO | Train Epoch: 0 [1004864/2339328 (43%)] Data (t): 0.035 Batch (t): 0.942, 67.1075/s LR: 0.000006 Logit Scale: 98.224 Contrastive_loss: 0.077078 (0.12933) Caption_loss: 3.9273 (4.6579) Loss: 4.0043 (4.7872) +2023-04-03,22:46:06 | INFO | Train Epoch: 0 [1011264/2339328 (43%)] Data (t): 0.035 Batch (t): 0.938, 67.7966/s LR: 0.000006 Logit Scale: 98.223 Contrastive_loss: 0.058083 (0.12888) Caption_loss: 4.6886 (4.6580) Loss: 4.7467 (4.7869) +2023-04-03,22:47:40 | INFO | Train Epoch: 0 [1017664/2339328 (44%)] Data (t): 0.035 Batch (t): 0.940, 68.5128/s LR: 0.000006 Logit Scale: 98.225 Contrastive_loss: 0.063434 (0.12847) Caption_loss: 5.1003 (4.6608) Loss: 5.1637 (4.7893) +2023-04-03,22:49:15 | INFO | Train Epoch: 0 [1024064/2339328 (44%)] Data (t): 0.035 Batch (t): 0.942, 67.4385/s LR: 0.000006 Logit Scale: 98.220 Contrastive_loss: 0.067709 (0.12809) Caption_loss: 4.5539 (4.6601) Loss: 4.6216 (4.7882) +2023-04-03,22:50:49 | INFO | Train Epoch: 0 [1030464/2339328 (44%)] Data (t): 0.035 Batch (t): 0.940, 67.7026/s LR: 0.000006 Logit Scale: 98.226 Contrastive_loss: 0.15432 (0.12825) Caption_loss: 4.8735 (4.6615) Loss: 5.0279 (4.7897) +2023-04-03,22:52:23 | INFO | Train Epoch: 0 [1036864/2339328 (44%)] Data (t): 0.035 Batch (t): 0.940, 67.5902/s LR: 0.000006 Logit Scale: 98.225 Contrastive_loss: 0.081764 (0.12797) Caption_loss: 4.3490 (4.6595) Loss: 4.4307 (4.7875) +2023-04-03,22:53:57 | INFO | Train Epoch: 0 [1043264/2339328 (45%)] Data (t): 0.036 Batch (t): 0.940, 69.1345/s LR: 0.000006 Logit Scale: 98.218 Contrastive_loss: 0.068167 (0.12760) Caption_loss: 4.6425 (4.6594) Loss: 4.7107 (4.7870) +2023-04-03,22:55:31 | INFO | Train Epoch: 0 [1049664/2339328 (45%)] Data (t): 0.035 Batch (t): 0.939, 68.1421/s LR: 0.000006 Logit Scale: 98.206 Contrastive_loss: 0.13341 (0.12764) Caption_loss: 5.1537 (4.6624) Loss: 5.2871 (4.7901) +2023-04-03,22:57:05 | INFO | Train Epoch: 0 [1056064/2339328 (45%)] Data (t): 0.035 Batch (t): 0.943, 67.4106/s LR: 0.000006 Logit Scale: 98.207 Contrastive_loss: 0.15319 (0.12779) Caption_loss: 4.5882 (4.6620) Loss: 4.7414 (4.7898) +2023-04-03,22:58:39 | INFO | Train Epoch: 0 [1062464/2339328 (45%)] Data (t): 0.035 Batch (t): 0.941, 67.6307/s LR: 0.000006 Logit Scale: 98.207 Contrastive_loss: 0.24076 (0.12847) Caption_loss: 4.9414 (4.6637) Loss: 5.1821 (4.7921) +2023-04-03,23:00:13 | INFO | Train Epoch: 0 [1068864/2339328 (46%)] Data (t): 0.035 Batch (t): 0.942, 68.8129/s LR: 0.000006 Logit Scale: 98.199 Contrastive_loss: 0.031119 (0.12789) Caption_loss: 5.3100 (4.6675) Loss: 5.3411 (4.7954) +2023-04-03,23:01:47 | INFO | Train Epoch: 0 [1075264/2339328 (46%)] Data (t): 0.035 Batch (t): 0.940, 68.5074/s LR: 0.000006 Logit Scale: 98.193 Contrastive_loss: 0.059641 (0.12749) Caption_loss: 3.9697 (4.6634) Loss: 4.0294 (4.7909) +2023-04-03,23:03:21 | INFO | Train Epoch: 0 [1081664/2339328 (46%)] Data (t): 0.036 Batch (t): 0.941, 67.6985/s LR: 0.000006 Logit Scale: 98.190 Contrastive_loss: 0.17920 (0.12779) Caption_loss: 5.0259 (4.6655) Loss: 5.2051 (4.7933) +2023-04-03,23:04:56 | INFO | Train Epoch: 0 [1088064/2339328 (47%)] Data (t): 0.035 Batch (t): 0.944, 67.9137/s LR: 0.000006 Logit Scale: 98.183 Contrastive_loss: 0.13079 (0.12781) Caption_loss: 4.4872 (4.6645) Loss: 4.6180 (4.7923) +2023-04-03,23:06:30 | INFO | Train Epoch: 0 [1094464/2339328 (47%)] Data (t): 0.036 Batch (t): 0.942, 67.6509/s LR: 0.000006 Logit Scale: 98.183 Contrastive_loss: 0.16524 (0.12803) Caption_loss: 4.5001 (4.6635) Loss: 4.6653 (4.7915) +2023-04-03,23:08:04 | INFO | Train Epoch: 0 [1100864/2339328 (47%)] Data (t): 0.035 Batch (t): 0.945, 68.8733/s LR: 0.000006 Logit Scale: 98.173 Contrastive_loss: 0.13664 (0.12808) Caption_loss: 5.6039 (4.6690) Loss: 5.7406 (4.7970) +2023-04-03,23:09:38 | INFO | Train Epoch: 0 [1107264/2339328 (47%)] Data (t): 0.035 Batch (t): 0.940, 67.9017/s LR: 0.000006 Logit Scale: 98.171 Contrastive_loss: 0.14255 (0.12816) Caption_loss: 4.9954 (4.6708) Loss: 5.1379 (4.7990) +2023-04-03,23:11:12 | INFO | Train Epoch: 0 [1113664/2339328 (48%)] Data (t): 0.035 Batch (t): 0.938, 68.0011/s LR: 0.000006 Logit Scale: 98.173 Contrastive_loss: 0.013064 (0.12750) Caption_loss: 4.1159 (4.6677) Loss: 4.1289 (4.7952) +2023-04-03,23:12:46 | INFO | Train Epoch: 0 [1120064/2339328 (48%)] Data (t): 0.035 Batch (t): 0.941, 69.3605/s LR: 0.000006 Logit Scale: 98.172 Contrastive_loss: 0.096206 (0.12732) Caption_loss: 5.0796 (4.6700) Loss: 5.1758 (4.7973) +2023-04-03,23:14:21 | INFO | Train Epoch: 0 [1126464/2339328 (48%)] Data (t): 0.035 Batch (t): 0.945, 68.2983/s LR: 0.000006 Logit Scale: 98.169 Contrastive_loss: 0.16654 (0.12754) Caption_loss: 6.3308 (4.6794) Loss: 6.4974 (4.8069) +2023-04-03,23:15:54 | INFO | Train Epoch: 0 [1132864/2339328 (48%)] Data (t): 0.035 Batch (t): 0.939, 69.0157/s LR: 0.000005 Logit Scale: 98.176 Contrastive_loss: 0.15817 (0.12772) Caption_loss: 5.0473 (4.6814) Loss: 5.2055 (4.8092) +2023-04-03,23:17:28 | INFO | Train Epoch: 0 [1139264/2339328 (49%)] Data (t): 0.035 Batch (t): 0.939, 68.2223/s LR: 0.000005 Logit Scale: 98.168 Contrastive_loss: 0.0063450 (0.12704) Caption_loss: 3.0580 (4.6724) Loss: 3.0643 (4.7994) +2023-04-03,23:19:03 | INFO | Train Epoch: 0 [1145664/2339328 (49%)] Data (t): 0.035 Batch (t): 0.943, 68.2305/s LR: 0.000005 Logit Scale: 98.162 Contrastive_loss: 0.20265 (0.12746) Caption_loss: 4.8314 (4.6733) Loss: 5.0340 (4.8007) +2023-04-03,23:20:37 | INFO | Train Epoch: 0 [1152064/2339328 (49%)] Data (t): 0.035 Batch (t): 0.940, 68.4923/s LR: 0.000005 Logit Scale: 98.157 Contrastive_loss: 0.18157 (0.12776) Caption_loss: 4.9889 (4.6750) Loss: 5.1705 (4.8028) +2023-04-03,23:22:11 | INFO | Train Epoch: 0 [1158464/2339328 (50%)] Data (t): 0.035 Batch (t): 0.941, 67.5322/s LR: 0.000005 Logit Scale: 98.161 Contrastive_loss: 0.054999 (0.12736) Caption_loss: 4.3786 (4.6734) Loss: 4.4336 (4.8007) +2023-04-03,23:23:45 | INFO | Train Epoch: 0 [1164864/2339328 (50%)] Data (t): 0.035 Batch (t): 0.943, 67.2607/s LR: 0.000005 Logit Scale: 98.157 Contrastive_loss: 0.024009 (0.12679) Caption_loss: 4.4919 (4.6724) Loss: 4.5159 (4.7992) +2023-04-03,23:25:19 | INFO | Train Epoch: 0 [1171264/2339328 (50%)] Data (t): 0.035 Batch (t): 0.941, 68.9141/s LR: 0.000005 Logit Scale: 98.162 Contrastive_loss: 0.093818 (0.12661) Caption_loss: 4.8324 (4.6733) Loss: 4.9262 (4.7999) +2023-04-03,23:26:53 | INFO | Train Epoch: 0 [1177664/2339328 (50%)] Data (t): 0.035 Batch (t): 0.943, 68.2623/s LR: 0.000005 Logit Scale: 98.165 Contrastive_loss: 0.11360 (0.12654) Caption_loss: 5.1448 (4.6758) Loss: 5.2584 (4.8023) +2023-04-03,23:28:28 | INFO | Train Epoch: 0 [1184064/2339328 (51%)] Data (t): 0.035 Batch (t): 0.941, 68.2139/s LR: 0.000005 Logit Scale: 98.161 Contrastive_loss: 0.041114 (0.12608) Caption_loss: 5.4969 (4.6802) Loss: 5.5380 (4.8063) +2023-04-03,23:30:02 | INFO | Train Epoch: 0 [1190464/2339328 (51%)] Data (t): 0.035 Batch (t): 0.942, 68.0099/s LR: 0.000005 Logit Scale: 98.161 Contrastive_loss: 0.085725 (0.12587) Caption_loss: 3.5010 (4.6739) Loss: 3.5867 (4.7998) +2023-04-03,23:31:36 | INFO | Train Epoch: 0 [1196864/2339328 (51%)] Data (t): 0.035 Batch (t): 0.945, 68.2348/s LR: 0.000005 Logit Scale: 98.160 Contrastive_loss: 0.037742 (0.12540) Caption_loss: 3.5435 (4.6679) Loss: 3.5812 (4.7933) +2023-04-03,23:33:10 | INFO | Train Epoch: 0 [1203264/2339328 (51%)] Data (t): 0.035 Batch (t): 0.936, 67.1773/s LR: 0.000005 Logit Scale: 98.160 Contrastive_loss: 0.033563 (0.12491) Caption_loss: 4.7493 (4.6683) Loss: 4.7829 (4.7932) +2023-04-03,23:34:44 | INFO | Train Epoch: 0 [1209664/2339328 (52%)] Data (t): 0.035 Batch (t): 0.942, 69.0927/s LR: 0.000005 Logit Scale: 98.162 Contrastive_loss: 0.034547 (0.12444) Caption_loss: 3.8028 (4.6638) Loss: 3.8373 (4.7882) +2023-04-03,23:36:18 | INFO | Train Epoch: 0 [1216064/2339328 (52%)] Data (t): 0.035 Batch (t): 0.939, 67.7789/s LR: 0.000005 Logit Scale: 98.161 Contrastive_loss: 0.11422 (0.12438) Caption_loss: 5.2669 (4.6669) Loss: 5.3811 (4.7913) +2023-04-03,23:37:52 | INFO | Train Epoch: 0 [1222464/2339328 (52%)] Data (t): 0.035 Batch (t): 0.938, 68.4086/s LR: 0.000005 Logit Scale: 98.155 Contrastive_loss: 0.15255 (0.12453) Caption_loss: 4.6662 (4.6669) Loss: 4.8187 (4.7915) +2023-04-03,23:39:26 | INFO | Train Epoch: 0 [1228864/2339328 (53%)] Data (t): 0.035 Batch (t): 0.943, 67.2524/s LR: 0.000005 Logit Scale: 98.152 Contrastive_loss: 0.082494 (0.12431) Caption_loss: 4.3463 (4.6653) Loss: 4.4288 (4.7896) +2023-04-03,23:41:00 | INFO | Train Epoch: 0 [1235264/2339328 (53%)] Data (t): 0.035 Batch (t): 0.941, 67.2621/s LR: 0.000005 Logit Scale: 98.148 Contrastive_loss: 0.049045 (0.12393) Caption_loss: 3.5428 (4.6595) Loss: 3.5918 (4.7834) +2023-04-03,23:42:34 | INFO | Train Epoch: 0 [1241664/2339328 (53%)] Data (t): 0.035 Batch (t): 0.941, 69.2047/s LR: 0.000005 Logit Scale: 98.140 Contrastive_loss: 0.11562 (0.12388) Caption_loss: 4.0538 (4.6564) Loss: 4.1694 (4.7803) +2023-04-03,23:44:09 | INFO | Train Epoch: 0 [1248064/2339328 (53%)] Data (t): 0.035 Batch (t): 0.943, 67.6952/s LR: 0.000005 Logit Scale: 98.140 Contrastive_loss: 0.034986 (0.12343) Caption_loss: 5.6354 (4.6614) Loss: 5.6704 (4.7848) +2023-04-03,23:45:43 | INFO | Train Epoch: 0 [1254464/2339328 (54%)] Data (t): 0.035 Batch (t): 0.940, 66.5082/s LR: 0.000005 Logit Scale: 98.139 Contrastive_loss: 0.076381 (0.12319) Caption_loss: 4.5966 (4.6610) Loss: 4.6730 (4.7842) +2023-04-03,23:47:17 | INFO | Train Epoch: 0 [1260864/2339328 (54%)] Data (t): 0.035 Batch (t): 0.940, 67.8501/s LR: 0.000005 Logit Scale: 98.134 Contrastive_loss: 0.10318 (0.12309) Caption_loss: 4.6134 (4.6608) Loss: 4.7166 (4.7839) +2023-04-03,23:48:51 | INFO | Train Epoch: 0 [1267264/2339328 (54%)] Data (t): 0.035 Batch (t): 0.939, 68.8922/s LR: 0.000005 Logit Scale: 98.134 Contrastive_loss: 0.15528 (0.12325) Caption_loss: 4.4105 (4.6595) Loss: 4.5658 (4.7828) +2023-04-03,23:50:24 | INFO | Train Epoch: 0 [1273664/2339328 (54%)] Data (t): 0.035 Batch (t): 0.939, 66.0705/s LR: 0.000005 Logit Scale: 98.130 Contrastive_loss: 0.10423 (0.12316) Caption_loss: 3.9744 (4.6561) Loss: 4.0786 (4.7793) +2023-04-03,23:51:59 | INFO | Train Epoch: 0 [1280064/2339328 (55%)] Data (t): 0.035 Batch (t): 0.941, 68.1993/s LR: 0.000004 Logit Scale: 98.129 Contrastive_loss: 0.092344 (0.12300) Caption_loss: 4.6712 (4.6562) Loss: 4.7635 (4.7792) +2023-04-03,23:53:33 | INFO | Train Epoch: 0 [1286464/2339328 (55%)] Data (t): 0.035 Batch (t): 0.943, 68.2392/s LR: 0.000004 Logit Scale: 98.133 Contrastive_loss: 0.12600 (0.12302) Caption_loss: 4.3640 (4.6547) Loss: 4.4900 (4.7778) +2023-04-03,23:55:07 | INFO | Train Epoch: 0 [1292864/2339328 (55%)] Data (t): 0.035 Batch (t): 0.940, 63.5269/s LR: 0.000004 Logit Scale: 98.134 Contrastive_loss: 0.14411 (0.12312) Caption_loss: 6.1533 (4.6621) Loss: 6.2974 (4.7852) +2023-04-03,23:56:41 | INFO | Train Epoch: 0 [1299264/2339328 (56%)] Data (t): 0.035 Batch (t): 0.942, 67.9596/s LR: 0.000004 Logit Scale: 98.140 Contrastive_loss: 0.14606 (0.12323) Caption_loss: 4.9248 (4.6634) Loss: 5.0708 (4.7866) +2023-04-03,23:58:16 | INFO | Train Epoch: 0 [1305664/2339328 (56%)] Data (t): 0.035 Batch (t): 0.945, 66.1504/s LR: 0.000004 Logit Scale: 98.136 Contrastive_loss: 0.093143 (0.12309) Caption_loss: 4.2559 (4.6614) Loss: 4.3490 (4.7845) +2023-04-03,23:59:50 | INFO | Train Epoch: 0 [1312064/2339328 (56%)] Data (t): 0.035 Batch (t): 0.942, 67.3537/s LR: 0.000004 Logit Scale: 98.132 Contrastive_loss: 0.074879 (0.12285) Caption_loss: 3.5698 (4.6561) Loss: 3.6446 (4.7790) +2023-04-04,00:01:24 | INFO | Train Epoch: 0 [1318464/2339328 (56%)] Data (t): 0.035 Batch (t): 0.940, 67.7069/s LR: 0.000004 Logit Scale: 98.133 Contrastive_loss: 0.038289 (0.12244) Caption_loss: 5.0794 (4.6582) Loss: 5.1177 (4.7806) +2023-04-04,00:02:58 | INFO | Train Epoch: 0 [1324864/2339328 (57%)] Data (t): 0.035 Batch (t): 0.939, 69.1634/s LR: 0.000004 Logit Scale: 98.129 Contrastive_loss: 0.015863 (0.12193) Caption_loss: 3.9219 (4.6546) Loss: 3.9377 (4.7766) +2023-04-04,00:04:31 | INFO | Train Epoch: 0 [1331264/2339328 (57%)] Data (t): 0.035 Batch (t): 0.938, 69.2776/s LR: 0.000004 Logit Scale: 98.120 Contrastive_loss: 0.078701 (0.12173) Caption_loss: 4.4846 (4.6538) Loss: 4.5633 (4.7755) +2023-04-04,00:06:06 | INFO | Train Epoch: 0 [1337664/2339328 (57%)] Data (t): 0.035 Batch (t): 0.944, 65.9350/s LR: 0.000004 Logit Scale: 98.117 Contrastive_loss: 0.097173 (0.12161) Caption_loss: 3.0319 (4.6461) Loss: 3.1290 (4.7677) +2023-04-04,00:07:40 | INFO | Train Epoch: 0 [1344064/2339328 (57%)] Data (t): 0.035 Batch (t): 0.943, 67.5842/s LR: 0.000004 Logit Scale: 98.120 Contrastive_loss: 0.10357 (0.12152) Caption_loss: 4.8736 (4.6472) Loss: 4.9772 (4.7687) +2023-04-04,00:09:14 | INFO | Train Epoch: 0 [1350464/2339328 (58%)] Data (t): 0.035 Batch (t): 0.942, 68.9436/s LR: 0.000004 Logit Scale: 98.115 Contrastive_loss: 0.092065 (0.12138) Caption_loss: 3.6905 (4.6427) Loss: 3.7825 (4.7640) +2023-04-04,00:10:48 | INFO | Train Epoch: 0 [1356864/2339328 (58%)] Data (t): 0.034 Batch (t): 0.941, 69.0781/s LR: 0.000004 Logit Scale: 98.111 Contrastive_loss: 0.10258 (0.12130) Caption_loss: 3.9191 (4.6393) Loss: 4.0217 (4.7606) +2023-04-04,00:12:22 | INFO | Train Epoch: 0 [1363264/2339328 (58%)] Data (t): 0.035 Batch (t): 0.938, 66.4283/s LR: 0.000004 Logit Scale: 98.109 Contrastive_loss: 0.097704 (0.12119) Caption_loss: 4.0099 (4.6363) Loss: 4.1076 (4.7575) +2023-04-04,00:13:56 | INFO | Train Epoch: 0 [1369664/2339328 (59%)] Data (t): 0.035 Batch (t): 0.938, 68.1453/s LR: 0.000004 Logit Scale: 98.114 Contrastive_loss: 0.14923 (0.12132) Caption_loss: 3.7915 (4.6324) Loss: 3.9407 (4.7537) +2023-04-04,00:15:30 | INFO | Train Epoch: 0 [1376064/2339328 (59%)] Data (t): 0.035 Batch (t): 0.937, 68.1921/s LR: 0.000004 Logit Scale: 98.110 Contrastive_loss: 0.17994 (0.12159) Caption_loss: 5.0360 (4.6343) Loss: 5.2159 (4.7558) +2023-04-04,00:17:04 | INFO | Train Epoch: 0 [1382464/2339328 (59%)] Data (t): 0.035 Batch (t): 0.944, 64.2189/s LR: 0.000004 Logit Scale: 98.111 Contrastive_loss: 0.097296 (0.12148) Caption_loss: 5.7091 (4.6392) Loss: 5.8064 (4.7607) +2023-04-04,00:18:39 | INFO | Train Epoch: 0 [1388864/2339328 (59%)] Data (t): 0.035 Batch (t): 0.950, 65.9530/s LR: 0.000004 Logit Scale: 98.109 Contrastive_loss: 0.15125 (0.12161) Caption_loss: 4.5473 (4.6388) Loss: 4.6985 (4.7604) +2023-04-04,00:20:13 | INFO | Train Epoch: 0 [1395264/2339328 (60%)] Data (t): 0.035 Batch (t): 0.943, 69.8436/s LR: 0.000004 Logit Scale: 98.108 Contrastive_loss: 0.15048 (0.12174) Caption_loss: 4.2716 (4.6371) Loss: 4.4221 (4.7589) +2023-04-04,00:21:48 | INFO | Train Epoch: 0 [1401664/2339328 (60%)] Data (t): 0.035 Batch (t): 0.944, 66.2132/s LR: 0.000004 Logit Scale: 98.106 Contrastive_loss: 0.16424 (0.12194) Caption_loss: 5.4241 (4.6407) Loss: 5.5883 (4.7626) +2023-04-04,00:23:22 | INFO | Train Epoch: 0 [1408064/2339328 (60%)] Data (t): 0.035 Batch (t): 0.946, 66.4072/s LR: 0.000004 Logit Scale: 98.108 Contrastive_loss: 0.090035 (0.12179) Caption_loss: 3.2081 (4.6342) Loss: 3.2982 (4.7560) +2023-04-04,00:24:57 | INFO | Train Epoch: 0 [1414464/2339328 (60%)] Data (t): 0.035 Batch (t): 0.941, 67.8025/s LR: 0.000004 Logit Scale: 98.110 Contrastive_loss: 0.070734 (0.12156) Caption_loss: 3.3736 (4.6285) Loss: 3.4444 (4.7501) +2023-04-04,00:26:32 | INFO | Train Epoch: 0 [1420864/2339328 (61%)] Data (t): 0.035 Batch (t): 0.953, 67.1135/s LR: 0.000004 Logit Scale: 98.107 Contrastive_loss: 0.067998 (0.12132) Caption_loss: 3.8836 (4.6252) Loss: 3.9516 (4.7465) +2023-04-04,00:28:08 | INFO | Train Epoch: 0 [1427264/2339328 (61%)] Data (t): 0.035 Batch (t): 0.960, 68.0416/s LR: 0.000003 Logit Scale: 98.105 Contrastive_loss: 0.072963 (0.12111) Caption_loss: 4.0145 (4.6225) Loss: 4.0874 (4.7436) +2023-04-04,00:29:43 | INFO | Train Epoch: 0 [1433664/2339328 (61%)] Data (t): 0.035 Batch (t): 0.952, 68.2999/s LR: 0.000003 Logit Scale: 98.101 Contrastive_loss: 0.062238 (0.12084) Caption_loss: 5.0004 (4.6241) Loss: 5.0627 (4.7450) +2023-04-04,00:31:17 | INFO | Train Epoch: 0 [1440064/2339328 (62%)] Data (t): 0.035 Batch (t): 0.936, 70.2629/s LR: 0.000003 Logit Scale: 98.099 Contrastive_loss: 0.19849 (0.12119) Caption_loss: 3.6622 (4.6199) Loss: 3.8607 (4.7411) +2023-04-04,00:32:48 | INFO | Train Epoch: 0 [1446464/2339328 (62%)] Data (t): 0.035 Batch (t): 0.912, 70.1916/s LR: 0.000003 Logit Scale: 98.097 Contrastive_loss: 0.043172 (0.12084) Caption_loss: 3.7559 (4.6161) Loss: 3.7991 (4.7369) +2023-04-04,00:34:19 | INFO | Train Epoch: 0 [1452864/2339328 (62%)] Data (t): 0.035 Batch (t): 0.909, 70.7415/s LR: 0.000003 Logit Scale: 98.094 Contrastive_loss: 0.033349 (0.12046) Caption_loss: 4.2578 (4.6145) Loss: 4.2911 (4.7350) +2023-04-04,00:35:49 | INFO | Train Epoch: 0 [1459264/2339328 (62%)] Data (t): 0.035 Batch (t): 0.908, 70.2028/s LR: 0.000003 Logit Scale: 98.097 Contrastive_loss: 0.086529 (0.12031) Caption_loss: 5.4012 (4.6179) Loss: 5.4877 (4.7383) +2023-04-04,00:37:20 | INFO | Train Epoch: 0 [1465664/2339328 (63%)] Data (t): 0.035 Batch (t): 0.910, 70.6061/s LR: 0.000003 Logit Scale: 98.098 Contrastive_loss: 0.16642 (0.12051) Caption_loss: 5.9873 (4.6239) Loss: 6.1537 (4.7444) +2023-04-04,00:38:52 | INFO | Train Epoch: 0 [1472064/2339328 (63%)] Data (t): 0.035 Batch (t): 0.915, 69.4966/s LR: 0.000003 Logit Scale: 98.096 Contrastive_loss: 0.11111 (0.12047) Caption_loss: 5.3422 (4.6270) Loss: 5.4534 (4.7475) +2023-04-04,00:40:23 | INFO | Train Epoch: 0 [1478464/2339328 (63%)] Data (t): 0.034 Batch (t): 0.909, 70.3113/s LR: 0.000003 Logit Scale: 98.098 Contrastive_loss: 0.25725 (0.12106) Caption_loss: 4.1680 (4.6250) Loss: 4.4252 (4.7461) +2023-04-04,00:41:54 | INFO | Train Epoch: 0 [1484864/2339328 (63%)] Data (t): 0.034 Batch (t): 0.908, 70.0570/s LR: 0.000003 Logit Scale: 98.094 Contrastive_loss: 0.042056 (0.12072) Caption_loss: 3.9336 (4.6221) Loss: 3.9757 (4.7428) +2023-04-04,00:43:25 | INFO | Train Epoch: 0 [1491264/2339328 (64%)] Data (t): 0.034 Batch (t): 0.913, 68.4202/s LR: 0.000003 Logit Scale: 98.097 Contrastive_loss: 0.059019 (0.12046) Caption_loss: 3.3839 (4.6168) Loss: 3.4429 (4.7372) +2023-04-04,00:44:56 | INFO | Train Epoch: 0 [1497664/2339328 (64%)] Data (t): 0.034 Batch (t): 0.907, 70.7199/s LR: 0.000003 Logit Scale: 98.094 Contrastive_loss: 0.15120 (0.12059) Caption_loss: 4.2162 (4.6151) Loss: 4.3674 (4.7357) +2023-04-04,00:46:26 | INFO | Train Epoch: 0 [1504064/2339328 (64%)] Data (t): 0.035 Batch (t): 0.908, 70.3467/s LR: 0.000003 Logit Scale: 98.097 Contrastive_loss: 0.099958 (0.12050) Caption_loss: 4.9872 (4.6166) Loss: 5.0871 (4.7371) +2023-04-04,00:47:57 | INFO | Train Epoch: 0 [1510464/2339328 (65%)] Data (t): 0.034 Batch (t): 0.907, 70.5684/s LR: 0.000003 Logit Scale: 98.098 Contrastive_loss: 0.11114 (0.12046) Caption_loss: 4.9881 (4.6182) Loss: 5.0992 (4.7387) +2023-04-04,00:49:28 | INFO | Train Epoch: 0 [1516864/2339328 (65%)] Data (t): 0.034 Batch (t): 0.911, 70.6381/s LR: 0.000003 Logit Scale: 98.093 Contrastive_loss: 0.086579 (0.12032) Caption_loss: 4.7726 (4.6189) Loss: 4.8592 (4.7392) +2023-04-04,00:50:59 | INFO | Train Epoch: 0 [1523264/2339328 (65%)] Data (t): 0.034 Batch (t): 0.912, 70.3864/s LR: 0.000003 Logit Scale: 98.089 Contrastive_loss: 0.17079 (0.12053) Caption_loss: 5.2876 (4.6217) Loss: 5.4584 (4.7422) +2023-04-04,00:52:31 | INFO | Train Epoch: 0 [1529664/2339328 (65%)] Data (t): 0.034 Batch (t): 0.917, 70.3289/s LR: 0.000003 Logit Scale: 98.088 Contrastive_loss: 0.090070 (0.12041) Caption_loss: 5.1797 (4.6240) Loss: 5.2698 (4.7444) +2023-04-04,00:54:02 | INFO | Train Epoch: 0 [1536064/2339328 (66%)] Data (t): 0.034 Batch (t): 0.910, 70.3606/s LR: 0.000003 Logit Scale: 98.088 Contrastive_loss: 0.11858 (0.12040) Caption_loss: 4.2299 (4.6223) Loss: 4.3485 (4.7427) +2023-04-04,00:55:33 | INFO | Train Epoch: 0 [1542464/2339328 (66%)] Data (t): 0.034 Batch (t): 0.908, 69.5144/s LR: 0.000003 Logit Scale: 98.092 Contrastive_loss: 0.24924 (0.12093) Caption_loss: 4.2151 (4.6207) Loss: 4.4644 (4.7416) +2023-04-04,00:57:05 | INFO | Train Epoch: 0 [1548864/2339328 (66%)] Data (t): 0.034 Batch (t): 0.915, 69.6275/s LR: 0.000003 Logit Scale: 98.091 Contrastive_loss: 0.041544 (0.12060) Caption_loss: 4.1029 (4.6185) Loss: 4.1444 (4.7391) +2023-04-04,00:58:36 | INFO | Train Epoch: 0 [1555264/2339328 (66%)] Data (t): 0.034 Batch (t): 0.919, 69.6853/s LR: 0.000003 Logit Scale: 98.094 Contrastive_loss: 0.13175 (0.12065) Caption_loss: 4.7598 (4.6191) Loss: 4.8916 (4.7398) +2023-04-04,01:00:08 | INFO | Train Epoch: 0 [1561664/2339328 (67%)] Data (t): 0.034 Batch (t): 0.912, 70.0644/s LR: 0.000003 Logit Scale: 98.094 Contrastive_loss: 0.047785 (0.12035) Caption_loss: 4.7343 (4.6196) Loss: 4.7821 (4.7399) +2023-04-04,01:01:39 | INFO | Train Epoch: 0 [1568064/2339328 (67%)] Data (t): 0.034 Batch (t): 0.910, 70.0296/s LR: 0.000003 Logit Scale: 98.091 Contrastive_loss: 0.042198 (0.12003) Caption_loss: 2.7125 (4.6118) Loss: 2.7547 (4.7319) +2023-04-04,01:03:10 | INFO | Train Epoch: 0 [1574464/2339328 (67%)] Data (t): 0.034 Batch (t): 0.912, 70.0018/s LR: 0.000003 Logit Scale: 98.091 Contrastive_loss: 0.080266 (0.11987) Caption_loss: 4.8594 (4.6128) Loss: 4.9397 (4.7327) +2023-04-04,01:04:41 | INFO | Train Epoch: 0 [1580864/2339328 (68%)] Data (t): 0.034 Batch (t): 0.914, 70.5494/s LR: 0.000003 Logit Scale: 98.091 Contrastive_loss: 0.058918 (0.11963) Caption_loss: 4.5818 (4.6127) Loss: 4.6407 (4.7323) +2023-04-04,01:06:13 | INFO | Train Epoch: 0 [1587264/2339328 (68%)] Data (t): 0.034 Batch (t): 0.914, 70.1643/s LR: 0.000002 Logit Scale: 98.092 Contrastive_loss: 0.091788 (0.11952) Caption_loss: 3.6488 (4.6088) Loss: 3.7406 (4.7284) +2023-04-04,01:07:44 | INFO | Train Epoch: 0 [1593664/2339328 (68%)] Data (t): 0.035 Batch (t): 0.911, 70.1721/s LR: 0.000002 Logit Scale: 98.089 Contrastive_loss: 0.099597 (0.11944) Caption_loss: 4.7496 (4.6094) Loss: 4.8492 (4.7288) +2023-04-04,01:09:15 | INFO | Train Epoch: 0 [1600064/2339328 (68%)] Data (t): 0.034 Batch (t): 0.908, 70.5634/s LR: 0.000002 Logit Scale: 98.089 Contrastive_loss: 0.13187 (0.11949) Caption_loss: 3.7057 (4.6058) Loss: 3.8376 (4.7253) +2023-04-04,01:10:46 | INFO | Train Epoch: 0 [1606464/2339328 (69%)] Data (t): 0.034 Batch (t): 0.912, 68.9455/s LR: 0.000002 Logit Scale: 98.093 Contrastive_loss: 0.083511 (0.11934) Caption_loss: 4.5096 (4.6054) Loss: 4.5931 (4.7248) +2023-04-04,01:12:17 | INFO | Train Epoch: 0 [1612864/2339328 (69%)] Data (t): 0.034 Batch (t): 0.908, 69.5692/s LR: 0.000002 Logit Scale: 98.093 Contrastive_loss: 0.10681 (0.11929) Caption_loss: 4.0349 (4.6032) Loss: 4.1417 (4.7225) +2023-04-04,01:13:48 | INFO | Train Epoch: 0 [1619264/2339328 (69%)] Data (t): 0.034 Batch (t): 0.910, 70.2307/s LR: 0.000002 Logit Scale: 98.093 Contrastive_loss: 0.11146 (0.11926) Caption_loss: 4.3959 (4.6023) Loss: 4.5073 (4.7216) +2023-04-04,01:15:19 | INFO | Train Epoch: 0 [1625664/2339328 (69%)] Data (t): 0.034 Batch (t): 0.910, 70.5274/s LR: 0.000002 Logit Scale: 98.091 Contrastive_loss: 0.041137 (0.11896) Caption_loss: 3.3928 (4.5976) Loss: 3.4340 (4.7166) +2023-04-04,01:16:50 | INFO | Train Epoch: 0 [1632064/2339328 (70%)] Data (t): 0.034 Batch (t): 0.915, 70.0233/s LR: 0.000002 Logit Scale: 98.088 Contrastive_loss: 0.038242 (0.11864) Caption_loss: 3.7355 (4.5942) Loss: 3.7738 (4.7129) +2023-04-04,01:18:22 | INFO | Train Epoch: 0 [1638464/2339328 (70%)] Data (t): 0.034 Batch (t): 0.917, 70.6810/s LR: 0.000002 Logit Scale: 98.086 Contrastive_loss: 0.22952 (0.11907) Caption_loss: 2.9775 (4.5879) Loss: 3.2070 (4.7070) +2023-04-04,01:19:53 | INFO | Train Epoch: 0 [1644864/2339328 (70%)] Data (t): 0.034 Batch (t): 0.908, 70.5802/s LR: 0.000002 Logit Scale: 98.086 Contrastive_loss: 0.11518 (0.11906) Caption_loss: 3.2679 (4.5828) Loss: 3.3831 (4.7019) +2023-04-04,01:21:23 | INFO | Train Epoch: 0 [1651264/2339328 (71%)] Data (t): 0.034 Batch (t): 0.907, 70.7650/s LR: 0.000002 Logit Scale: 98.088 Contrastive_loss: 0.11272 (0.11903) Caption_loss: 4.6380 (4.5830) Loss: 4.7507 (4.7021) +2023-04-04,01:22:54 | INFO | Train Epoch: 0 [1657664/2339328 (71%)] Data (t): 0.034 Batch (t): 0.906, 70.2317/s LR: 0.000002 Logit Scale: 98.088 Contrastive_loss: 0.11580 (0.11902) Caption_loss: 4.3741 (4.5822) Loss: 4.4899 (4.7013) +2023-04-04,01:24:25 | INFO | Train Epoch: 0 [1664064/2339328 (71%)] Data (t): 0.034 Batch (t): 0.908, 70.2172/s LR: 0.000002 Logit Scale: 98.086 Contrastive_loss: 0.031874 (0.11869) Caption_loss: 4.1902 (4.5807) Loss: 4.2221 (4.6994) +2023-04-04,01:25:56 | INFO | Train Epoch: 0 [1670464/2339328 (71%)] Data (t): 0.034 Batch (t): 0.910, 70.6303/s LR: 0.000002 Logit Scale: 98.086 Contrastive_loss: 0.071471 (0.11851) Caption_loss: 4.1219 (4.5790) Loss: 4.1934 (4.6975) +2023-04-04,01:27:27 | INFO | Train Epoch: 0 [1676864/2339328 (72%)] Data (t): 0.035 Batch (t): 0.912, 70.0406/s LR: 0.000002 Logit Scale: 98.087 Contrastive_loss: 0.085026 (0.11838) Caption_loss: 4.0089 (4.5768) Loss: 4.0939 (4.6952) +2023-04-04,01:28:58 | INFO | Train Epoch: 0 [1683264/2339328 (72%)] Data (t): 0.034 Batch (t): 0.914, 70.3173/s LR: 0.000002 Logit Scale: 98.085 Contrastive_loss: 0.11017 (0.11835) Caption_loss: 3.7601 (4.5737) Loss: 3.8703 (4.6921) +2023-04-04,01:30:30 | INFO | Train Epoch: 0 [1689664/2339328 (72%)] Data (t): 0.034 Batch (t): 0.913, 70.1105/s LR: 0.000002 Logit Scale: 98.085 Contrastive_loss: 0.11447 (0.11833) Caption_loss: 4.0318 (4.5717) Loss: 4.1463 (4.6900) +2023-04-04,01:32:00 | INFO | Train Epoch: 0 [1696064/2339328 (73%)] Data (t): 0.035 Batch (t): 0.908, 70.2987/s LR: 0.000002 Logit Scale: 98.085 Contrastive_loss: 0.040130 (0.11804) Caption_loss: 4.3643 (4.5709) Loss: 4.4044 (4.6889) +2023-04-04,01:33:31 | INFO | Train Epoch: 0 [1702464/2339328 (73%)] Data (t): 0.035 Batch (t): 0.910, 70.1269/s LR: 0.000002 Logit Scale: 98.084 Contrastive_loss: 0.13648 (0.11811) Caption_loss: 5.4221 (4.5741) Loss: 5.5586 (4.6922) +2023-04-04,01:35:04 | INFO | Train Epoch: 0 [1708864/2339328 (73%)] Data (t): 0.035 Batch (t): 0.922, 70.6477/s LR: 0.000002 Logit Scale: 98.083 Contrastive_loss: 0.12765 (0.11814) Caption_loss: 4.1701 (4.5726) Loss: 4.2978 (4.6907) +2023-04-04,01:36:35 | INFO | Train Epoch: 0 [1715264/2339328 (73%)] Data (t): 0.035 Batch (t): 0.911, 70.6179/s LR: 0.000002 Logit Scale: 98.082 Contrastive_loss: 0.076111 (0.11799) Caption_loss: 4.2682 (4.5714) Loss: 4.3443 (4.6894) +2023-04-04,01:38:07 | INFO | Train Epoch: 0 [1721664/2339328 (74%)] Data (t): 0.035 Batch (t): 0.919, 69.5903/s LR: 0.000002 Logit Scale: 98.085 Contrastive_loss: 0.041407 (0.11770) Caption_loss: 5.0359 (4.5732) Loss: 5.0774 (4.6909) +2023-04-04,01:39:37 | INFO | Train Epoch: 0 [1728064/2339328 (74%)] Data (t): 0.034 Batch (t): 0.908, 70.6506/s LR: 0.000002 Logit Scale: 98.084 Contrastive_loss: 0.058985 (0.11749) Caption_loss: 4.0577 (4.5713) Loss: 4.1167 (4.6888) +2023-04-04,01:41:08 | INFO | Train Epoch: 0 [1734464/2339328 (74%)] Data (t): 0.035 Batch (t): 0.908, 70.4013/s LR: 0.000002 Logit Scale: 98.085 Contrastive_loss: 0.034758 (0.11718) Caption_loss: 3.8391 (4.5686) Loss: 3.8738 (4.6858) +2023-04-04,01:42:39 | INFO | Train Epoch: 0 [1740864/2339328 (74%)] Data (t): 0.034 Batch (t): 0.909, 70.2568/s LR: 0.000002 Logit Scale: 98.084 Contrastive_loss: 0.11134 (0.11716) Caption_loss: 4.2161 (4.5673) Loss: 4.3274 (4.6844) +2023-04-04,01:44:10 | INFO | Train Epoch: 0 [1747264/2339328 (75%)] Data (t): 0.034 Batch (t): 0.909, 70.1791/s LR: 0.000002 Logit Scale: 98.081 Contrastive_loss: 0.10486 (0.11712) Caption_loss: 3.5987 (4.5637) Loss: 3.7036 (4.6809) +2023-04-04,01:45:41 | INFO | Train Epoch: 0 [1753664/2339328 (75%)] Data (t): 0.034 Batch (t): 0.912, 70.2095/s LR: 0.000002 Logit Scale: 98.082 Contrastive_loss: 0.22048 (0.11749) Caption_loss: 3.7396 (4.5608) Loss: 3.9601 (4.6782) +2023-04-04,01:47:13 | INFO | Train Epoch: 0 [1760064/2339328 (75%)] Data (t): 0.035 Batch (t): 0.915, 69.0297/s LR: 0.000002 Logit Scale: 98.083 Contrastive_loss: 0.13208 (0.11755) Caption_loss: 5.3019 (4.5634) Loss: 5.4340 (4.6810) +2023-04-04,01:48:45 | INFO | Train Epoch: 0 [1766464/2339328 (76%)] Data (t): 0.034 Batch (t): 0.921, 69.3648/s LR: 0.000001 Logit Scale: 98.082 Contrastive_loss: 0.12418 (0.11757) Caption_loss: 4.4198 (4.5629) Loss: 4.5440 (4.6805) +2023-04-04,01:50:16 | INFO | Train Epoch: 0 [1772864/2339328 (76%)] Data (t): 0.034 Batch (t): 0.914, 70.7209/s LR: 0.000001 Logit Scale: 98.081 Contrastive_loss: 0.10184 (0.11751) Caption_loss: 4.3839 (4.5623) Loss: 4.4858 (4.6798) +2023-04-04,01:51:48 | INFO | Train Epoch: 0 [1779264/2339328 (76%)] Data (t): 0.034 Batch (t): 0.914, 70.2783/s LR: 0.000001 Logit Scale: 98.080 Contrastive_loss: 0.047511 (0.11726) Caption_loss: 4.5713 (4.5623) Loss: 4.6188 (4.6796) +2023-04-04,01:53:19 | INFO | Train Epoch: 0 [1785664/2339328 (76%)] Data (t): 0.034 Batch (t): 0.913, 70.2656/s LR: 0.000001 Logit Scale: 98.078 Contrastive_loss: 0.14062 (0.11735) Caption_loss: 4.1591 (4.5609) Loss: 4.2997 (4.6782) +2023-04-04,01:54:50 | INFO | Train Epoch: 0 [1792064/2339328 (77%)] Data (t): 0.034 Batch (t): 0.910, 69.7310/s LR: 0.000001 Logit Scale: 98.078 Contrastive_loss: 0.051607 (0.11711) Caption_loss: 4.0391 (4.5590) Loss: 4.0907 (4.6761) +2023-04-04,01:56:21 | INFO | Train Epoch: 0 [1798464/2339328 (77%)] Data (t): 0.034 Batch (t): 0.912, 70.2808/s LR: 0.000001 Logit Scale: 98.078 Contrastive_loss: 0.054862 (0.11689) Caption_loss: 4.5864 (4.5591) Loss: 4.6413 (4.6760) +2023-04-04,01:57:52 | INFO | Train Epoch: 0 [1804864/2339328 (77%)] Data (t): 0.035 Batch (t): 0.911, 70.1208/s LR: 0.000001 Logit Scale: 98.080 Contrastive_loss: 0.19572 (0.11717) Caption_loss: 4.4117 (4.5586) Loss: 4.6075 (4.6758) +2023-04-04,01:59:23 | INFO | Train Epoch: 0 [1811264/2339328 (77%)] Data (t): 0.034 Batch (t): 0.912, 70.6843/s LR: 0.000001 Logit Scale: 98.081 Contrastive_loss: 0.19337 (0.11744) Caption_loss: 3.4808 (4.5548) Loss: 3.6742 (4.6722) +2023-04-04,02:00:55 | INFO | Train Epoch: 0 [1817664/2339328 (78%)] Data (t): 0.034 Batch (t): 0.913, 70.3219/s LR: 0.000001 Logit Scale: 98.081 Contrastive_loss: 0.20918 (0.11776) Caption_loss: 4.0498 (4.5530) Loss: 4.2589 (4.6708) +2023-04-04,02:02:26 | INFO | Train Epoch: 0 [1824064/2339328 (78%)] Data (t): 0.034 Batch (t): 0.911, 69.0664/s LR: 0.000001 Logit Scale: 98.078 Contrastive_loss: 0.11556 (0.11775) Caption_loss: 4.5917 (4.5532) Loss: 4.7072 (4.6709) +2023-04-04,02:03:57 | INFO | Train Epoch: 0 [1830464/2339328 (78%)] Data (t): 0.034 Batch (t): 0.911, 69.3040/s LR: 0.000001 Logit Scale: 98.078 Contrastive_loss: 0.082823 (0.11763) Caption_loss: 3.9453 (4.5510) Loss: 4.0281 (4.6687) +2023-04-04,02:05:28 | INFO | Train Epoch: 0 [1836864/2339328 (79%)] Data (t): 0.034 Batch (t): 0.916, 70.2133/s LR: 0.000001 Logit Scale: 98.078 Contrastive_loss: 0.059952 (0.11743) Caption_loss: 4.6898 (4.5515) Loss: 4.7498 (4.6689) +2023-04-04,02:06:59 | INFO | Train Epoch: 0 [1843264/2339328 (79%)] Data (t): 0.034 Batch (t): 0.909, 70.6533/s LR: 0.000001 Logit Scale: 98.077 Contrastive_loss: 0.10949 (0.11740) Caption_loss: 3.8024 (4.5489) Loss: 3.9119 (4.6663) +2023-04-04,02:08:31 | INFO | Train Epoch: 0 [1849664/2339328 (79%)] Data (t): 0.034 Batch (t): 0.912, 70.1645/s LR: 0.000001 Logit Scale: 98.079 Contrastive_loss: 0.14553 (0.11750) Caption_loss: 4.5680 (4.5490) Loss: 4.7135 (4.6665) +2023-04-04,02:10:02 | INFO | Train Epoch: 0 [1856064/2339328 (79%)] Data (t): 0.034 Batch (t): 0.911, 70.0686/s LR: 0.000001 Logit Scale: 98.078 Contrastive_loss: 0.17903 (0.11771) Caption_loss: 5.4215 (4.5520) Loss: 5.6006 (4.6697) +2023-04-04,02:11:32 | INFO | Train Epoch: 0 [1862464/2339328 (80%)] Data (t): 0.034 Batch (t): 0.908, 68.6974/s LR: 0.000001 Logit Scale: 98.076 Contrastive_loss: 0.049646 (0.11748) Caption_loss: 3.7908 (4.5494) Loss: 3.8404 (4.6669) +2023-04-04,02:13:04 | INFO | Train Epoch: 0 [1868864/2339328 (80%)] Data (t): 0.034 Batch (t): 0.911, 70.4766/s LR: 0.000001 Logit Scale: 98.078 Contrastive_loss: 0.19376 (0.11774) Caption_loss: 5.3455 (4.5521) Loss: 5.5392 (4.6698) +2023-04-04,02:14:34 | INFO | Train Epoch: 0 [1875264/2339328 (80%)] Data (t): 0.034 Batch (t): 0.908, 70.3825/s LR: 0.000001 Logit Scale: 98.079 Contrastive_loss: 0.065229 (0.11756) Caption_loss: 4.1519 (4.5507) Loss: 4.2171 (4.6683) +2023-04-04,02:16:06 | INFO | Train Epoch: 0 [1881664/2339328 (80%)] Data (t): 0.034 Batch (t): 0.913, 70.6617/s LR: 0.000001 Logit Scale: 98.079 Contrastive_loss: 0.25323 (0.11802) Caption_loss: 5.2817 (4.5532) Loss: 5.5349 (4.6712) +2023-04-04,02:17:37 | INFO | Train Epoch: 0 [1888064/2339328 (81%)] Data (t): 0.034 Batch (t): 0.912, 70.8114/s LR: 0.000001 Logit Scale: 98.079 Contrastive_loss: 0.098962 (0.11795) Caption_loss: 4.1772 (4.5519) Loss: 4.2762 (4.6699) +2023-04-04,02:19:08 | INFO | Train Epoch: 0 [1894464/2339328 (81%)] Data (t): 0.034 Batch (t): 0.908, 70.8363/s LR: 0.000001 Logit Scale: 98.079 Contrastive_loss: 0.061947 (0.11777) Caption_loss: 5.1147 (4.5538) Loss: 5.1766 (4.6716) +2023-04-04,02:20:39 | INFO | Train Epoch: 0 [1900864/2339328 (81%)] Data (t): 0.034 Batch (t): 0.911, 70.1473/s LR: 0.000001 Logit Scale: 98.078 Contrastive_loss: 0.15302 (0.11788) Caption_loss: 3.1362 (4.5491) Loss: 3.2893 (4.6670) +2023-04-04,02:22:10 | INFO | Train Epoch: 0 [1907264/2339328 (82%)] Data (t): 0.034 Batch (t): 0.912, 70.3779/s LR: 0.000001 Logit Scale: 98.077 Contrastive_loss: 0.0028556 (0.11750) Caption_loss: 2.7693 (4.5431) Loss: 2.7721 (4.6606) +2023-04-04,02:23:41 | INFO | Train Epoch: 0 [1913664/2339328 (82%)] Data (t): 0.035 Batch (t): 0.910, 70.7653/s LR: 0.000001 Logit Scale: 98.076 Contrastive_loss: 0.038574 (0.11724) Caption_loss: 3.9175 (4.5410) Loss: 3.9561 (4.6583) +2023-04-04,02:25:12 | INFO | Train Epoch: 0 [1920064/2339328 (82%)] Data (t): 0.035 Batch (t): 0.910, 70.9444/s LR: 0.000001 Logit Scale: 98.077 Contrastive_loss: 0.17941 (0.11744) Caption_loss: 5.5761 (4.5445) Loss: 5.7555 (4.6619) +2023-04-04,02:26:43 | INFO | Train Epoch: 0 [1926464/2339328 (82%)] Data (t): 0.034 Batch (t): 0.910, 70.6951/s LR: 0.000001 Logit Scale: 98.077 Contrastive_loss: 0.16964 (0.11762) Caption_loss: 4.1521 (4.5432) Loss: 4.3218 (4.6608) +2023-04-04,02:28:15 | INFO | Train Epoch: 0 [1932864/2339328 (83%)] Data (t): 0.035 Batch (t): 0.917, 70.9279/s LR: 0.000001 Logit Scale: 98.077 Contrastive_loss: 0.050383 (0.11739) Caption_loss: 3.8716 (4.5410) Loss: 3.9219 (4.6584) +2023-04-04,02:29:45 | INFO | Train Epoch: 0 [1939264/2339328 (83%)] Data (t): 0.034 Batch (t): 0.908, 70.1909/s LR: 0.000001 Logit Scale: 98.076 Contrastive_loss: 0.13851 (0.11746) Caption_loss: 3.8725 (4.5388) Loss: 4.0110 (4.6562) +2023-04-04,02:31:17 | INFO | Train Epoch: 0 [1945664/2339328 (83%)] Data (t): 0.034 Batch (t): 0.920, 68.6300/s LR: 0.000001 Logit Scale: 98.077 Contrastive_loss: 0.13609 (0.11752) Caption_loss: 4.7109 (4.5393) Loss: 4.8470 (4.6569) +2023-04-04,02:32:48 | INFO | Train Epoch: 0 [1952064/2339328 (83%)] Data (t): 0.034 Batch (t): 0.910, 69.0130/s LR: 0.000001 Logit Scale: 98.076 Contrastive_loss: 0.11716 (0.11752) Caption_loss: 4.8710 (4.5404) Loss: 4.9882 (4.6579) +2023-04-04,02:34:20 | INFO | Train Epoch: 0 [1958464/2339328 (84%)] Data (t): 0.035 Batch (t): 0.911, 70.4615/s LR: 0.000001 Logit Scale: 98.076 Contrastive_loss: 0.12318 (0.11754) Caption_loss: 4.7759 (4.5412) Loss: 4.8990 (4.6587) +2023-04-04,02:35:51 | INFO | Train Epoch: 0 [1964864/2339328 (84%)] Data (t): 0.034 Batch (t): 0.910, 70.5368/s LR: 0.000001 Logit Scale: 98.076 Contrastive_loss: 0.039181 (0.11729) Caption_loss: 5.1599 (4.5432) Loss: 5.1991 (4.6605) +2023-04-04,02:37:21 | INFO | Train Epoch: 0 [1971264/2339328 (84%)] Data (t): 0.034 Batch (t): 0.908, 70.2376/s LR: 0.000001 Logit Scale: 98.076 Contrastive_loss: 0.029271 (0.11700) Caption_loss: 5.1255 (4.5451) Loss: 5.1548 (4.6621) +2023-04-04,02:38:53 | INFO | Train Epoch: 0 [1977664/2339328 (85%)] Data (t): 0.034 Batch (t): 0.913, 70.7714/s LR: 0.000001 Logit Scale: 98.075 Contrastive_loss: 0.032001 (0.11673) Caption_loss: 2.5713 (4.5387) Loss: 2.6033 (4.6554) +2023-04-04,02:40:23 | INFO | Train Epoch: 0 [1984064/2339328 (85%)] Data (t): 0.034 Batch (t): 0.909, 70.5275/s LR: 0.000001 Logit Scale: 98.076 Contrastive_loss: 0.097816 (0.11667) Caption_loss: 4.5884 (4.5389) Loss: 4.6862 (4.6555) +2023-04-04,02:41:54 | INFO | Train Epoch: 0 [1990464/2339328 (85%)] Data (t): 0.034 Batch (t): 0.908, 70.9234/s LR: 0.000001 Logit Scale: 98.076 Contrastive_loss: 0.034996 (0.11641) Caption_loss: 4.1875 (4.5377) Loss: 4.2225 (4.6542) +2023-04-04,02:43:26 | INFO | Train Epoch: 0 [1996864/2339328 (85%)] Data (t): 0.034 Batch (t): 0.920, 69.4768/s LR: 0.000001 Logit Scale: 98.075 Contrastive_loss: 0.034851 (0.11615) Caption_loss: 3.9966 (4.5360) Loss: 4.0314 (4.6522) +2023-04-04,02:44:58 | INFO | Train Epoch: 0 [2003264/2339328 (86%)] Data (t): 0.034 Batch (t): 0.916, 70.5068/s LR: 0.000001 Logit Scale: 98.075 Contrastive_loss: 0.092273 (0.11607) Caption_loss: 4.7521 (4.5367) Loss: 4.8444 (4.6528) +2023-04-04,02:46:29 | INFO | Train Epoch: 0 [2009664/2339328 (86%)] Data (t): 0.034 Batch (t): 0.911, 70.4748/s LR: 0.000001 Logit Scale: 98.075 Contrastive_loss: 0.25885 (0.11652) Caption_loss: 4.7827 (4.5375) Loss: 5.0416 (4.6540) +2023-04-04,02:48:00 | INFO | Train Epoch: 0 [2016064/2339328 (86%)] Data (t): 0.034 Batch (t): 0.910, 70.8257/s LR: 0.000000 Logit Scale: 98.075 Contrastive_loss: 0.032912 (0.11626) Caption_loss: 5.4411 (4.5403) Loss: 5.4740 (4.6566) +2023-04-04,02:49:31 | INFO | Train Epoch: 0 [2022464/2339328 (86%)] Data (t): 0.034 Batch (t): 0.908, 70.7422/s LR: 0.000000 Logit Scale: 98.075 Contrastive_loss: 0.19388 (0.11650) Caption_loss: 2.6776 (4.5345) Loss: 2.8715 (4.6510) +2023-04-04,02:51:01 | INFO | Train Epoch: 0 [2028864/2339328 (87%)] Data (t): 0.034 Batch (t): 0.907, 70.6738/s LR: 0.000000 Logit Scale: 98.075 Contrastive_loss: 0.058469 (0.11632) Caption_loss: 3.4558 (4.5311) Loss: 3.5143 (4.6474) +2023-04-04,02:52:32 | INFO | Train Epoch: 0 [2035264/2339328 (87%)] Data (t): 0.034 Batch (t): 0.909, 70.1917/s LR: 0.000000 Logit Scale: 98.074 Contrastive_loss: 0.080571 (0.11621) Caption_loss: 5.0545 (4.5327) Loss: 5.1351 (4.6489) +2023-04-04,02:54:03 | INFO | Train Epoch: 0 [2041664/2339328 (87%)] Data (t): 0.034 Batch (t): 0.910, 68.2158/s LR: 0.000000 Logit Scale: 98.074 Contrastive_loss: 0.13244 (0.11626) Caption_loss: 4.4484 (4.5325) Loss: 4.5808 (4.6487) +2023-04-04,02:55:36 | INFO | Train Epoch: 0 [2048064/2339328 (88%)] Data (t): 0.034 Batch (t): 0.926, 68.4696/s LR: 0.000000 Logit Scale: 98.074 Contrastive_loss: 0.0084866 (0.11592) Caption_loss: 4.7537 (4.5331) Loss: 4.7622 (4.6491) +2023-04-04,02:57:07 | INFO | Train Epoch: 0 [2054464/2339328 (88%)] Data (t): 0.034 Batch (t): 0.914, 70.5951/s LR: 0.000000 Logit Scale: 98.074 Contrastive_loss: 0.028297 (0.11565) Caption_loss: 4.3218 (4.5325) Loss: 4.3501 (4.6481) +2023-04-04,02:58:38 | INFO | Train Epoch: 0 [2060864/2339328 (88%)] Data (t): 0.035 Batch (t): 0.911, 70.2526/s LR: 0.000000 Logit Scale: 98.074 Contrastive_loss: 0.030086 (0.11539) Caption_loss: 4.5526 (4.5326) Loss: 4.5827 (4.6479) +2023-04-04,03:00:10 | INFO | Train Epoch: 0 [2067264/2339328 (88%)] Data (t): 0.034 Batch (t): 0.918, 68.5297/s LR: 0.000000 Logit Scale: 98.074 Contrastive_loss: 0.076550 (0.11527) Caption_loss: 4.7929 (4.5334) Loss: 4.8695 (4.6486) +2023-04-04,03:01:42 | INFO | Train Epoch: 0 [2073664/2339328 (89%)] Data (t): 0.034 Batch (t): 0.916, 70.2666/s LR: 0.000000 Logit Scale: 98.074 Contrastive_loss: 0.058970 (0.11509) Caption_loss: 3.4507 (4.5300) Loss: 3.5097 (4.6451) +2023-04-04,03:03:13 | INFO | Train Epoch: 0 [2080064/2339328 (89%)] Data (t): 0.035 Batch (t): 0.910, 70.5705/s LR: 0.000000 Logit Scale: 98.074 Contrastive_loss: 0.070600 (0.11496) Caption_loss: 3.5614 (4.5271) Loss: 3.6320 (4.6420) +2023-04-04,03:04:44 | INFO | Train Epoch: 0 [2086464/2339328 (89%)] Data (t): 0.035 Batch (t): 0.911, 70.0446/s LR: 0.000000 Logit Scale: 98.074 Contrastive_loss: 0.090012 (0.11488) Caption_loss: 3.5666 (4.5241) Loss: 3.6566 (4.6390) +2023-04-04,03:06:15 | INFO | Train Epoch: 0 [2092864/2339328 (89%)] Data (t): 0.035 Batch (t): 0.909, 70.2408/s LR: 0.000000 Logit Scale: 98.074 Contrastive_loss: 0.031363 (0.11463) Caption_loss: 4.3739 (4.5237) Loss: 4.4052 (4.6383) +2023-04-04,03:07:46 | INFO | Train Epoch: 0 [2099264/2339328 (90%)] Data (t): 0.035 Batch (t): 0.912, 70.0765/s LR: 0.000000 Logit Scale: 98.074 Contrastive_loss: 0.073017 (0.11450) Caption_loss: 4.6696 (4.5241) Loss: 4.7426 (4.6386) +2023-04-04,03:09:17 | INFO | Train Epoch: 0 [2105664/2339328 (90%)] Data (t): 0.035 Batch (t): 0.909, 70.5599/s LR: 0.000000 Logit Scale: 98.074 Contrastive_loss: 0.032636 (0.11425) Caption_loss: 4.9485 (4.5254) Loss: 4.9811 (4.6396) +2023-04-04,03:10:48 | INFO | Train Epoch: 0 [2112064/2339328 (90%)] Data (t): 0.035 Batch (t): 0.911, 69.9306/s LR: 0.000000 Logit Scale: 98.074 Contrastive_loss: 0.045493 (0.11404) Caption_loss: 3.3426 (4.5218) Loss: 3.3881 (4.6359) +2023-04-04,03:12:19 | INFO | Train Epoch: 0 [2118464/2339328 (91%)] Data (t): 0.035 Batch (t): 0.914, 70.6173/s LR: 0.000000 Logit Scale: 98.074 Contrastive_loss: 0.090746 (0.11397) Caption_loss: 4.1003 (4.5205) Loss: 4.1911 (4.6345) +2023-04-04,03:13:50 | INFO | Train Epoch: 0 [2124864/2339328 (91%)] Data (t): 0.035 Batch (t): 0.910, 70.3725/s LR: 0.000000 Logit Scale: 98.074 Contrastive_loss: 0.023748 (0.11370) Caption_loss: 4.2912 (4.5199) Loss: 4.3150 (4.6336) +2023-04-04,03:15:22 | INFO | Train Epoch: 0 [2131264/2339328 (91%)] Data (t): 0.034 Batch (t): 0.912, 70.1610/s LR: 0.000000 Logit Scale: 98.074 Contrastive_loss: 0.074120 (0.11358) Caption_loss: 4.9510 (4.5211) Loss: 5.0251 (4.6347) +2023-04-04,03:16:53 | INFO | Train Epoch: 0 [2137664/2339328 (91%)] Data (t): 0.034 Batch (t): 0.910, 70.0682/s LR: 0.000000 Logit Scale: 98.074 Contrastive_loss: 0.041030 (0.11337) Caption_loss: 4.3081 (4.5205) Loss: 4.3491 (4.6339) +2023-04-04,03:18:24 | INFO | Train Epoch: 0 [2144064/2339328 (92%)] Data (t): 0.034 Batch (t): 0.910, 70.4572/s LR: 0.000000 Logit Scale: 98.074 Contrastive_loss: 0.079102 (0.11327) Caption_loss: 5.0804 (4.5222) Loss: 5.1595 (4.6354) +2023-04-04,03:19:54 | INFO | Train Epoch: 0 [2150464/2339328 (92%)] Data (t): 0.034 Batch (t): 0.907, 68.8772/s LR: 0.000000 Logit Scale: 98.074 Contrastive_loss: 0.047561 (0.11307) Caption_loss: 4.3902 (4.5218) Loss: 4.4378 (4.6349) +2023-04-04,03:21:25 | INFO | Train Epoch: 0 [2156864/2339328 (92%)] Data (t): 0.034 Batch (t): 0.911, 69.9672/s LR: 0.000000 Logit Scale: 98.074 Contrastive_loss: 0.076220 (0.11296) Caption_loss: 3.7061 (4.5194) Loss: 3.7823 (4.6323) +2023-04-04,03:22:56 | INFO | Train Epoch: 0 [2163264/2339328 (92%)] Data (t): 0.034 Batch (t): 0.910, 69.9353/s LR: 0.000000 Logit Scale: 98.074 Contrastive_loss: 0.18567 (0.11318) Caption_loss: 4.2466 (4.5186) Loss: 4.4323 (4.6317) +2023-04-04,03:24:28 | INFO | Train Epoch: 0 [2169664/2339328 (93%)] Data (t): 0.034 Batch (t): 0.911, 69.1099/s LR: 0.000000 Logit Scale: 98.074 Contrastive_loss: 0.031630 (0.11294) Caption_loss: 3.2345 (4.5148) Loss: 3.2661 (4.6277) +2023-04-04,03:25:58 | INFO | Train Epoch: 0 [2176064/2339328 (93%)] Data (t): 0.034 Batch (t): 0.909, 69.9560/s LR: 0.000000 Logit Scale: 98.074 Contrastive_loss: 0.11162 (0.11293) Caption_loss: 4.9736 (4.5161) Loss: 5.0852 (4.6291) +2023-04-04,03:27:29 | INFO | Train Epoch: 0 [2182464/2339328 (93%)] Data (t): 0.034 Batch (t): 0.908, 69.9808/s LR: 0.000000 Logit Scale: 98.074 Contrastive_loss: 0.25202 (0.11334) Caption_loss: 5.8623 (4.5201) Loss: 6.1143 (4.6334) +2023-04-04,03:29:00 | INFO | Train Epoch: 0 [2188864/2339328 (94%)] Data (t): 0.034 Batch (t): 0.908, 70.6005/s LR: 0.000000 Logit Scale: 98.074 Contrastive_loss: 0.18918 (0.11356) Caption_loss: 5.4699 (4.5228) Loss: 5.6590 (4.6364) +2023-04-04,03:30:31 | INFO | Train Epoch: 0 [2195264/2339328 (94%)] Data (t): 0.034 Batch (t): 0.907, 70.4619/s LR: 0.000000 Logit Scale: 98.074 Contrastive_loss: 0.31559 (0.11415) Caption_loss: 4.4259 (4.5226) Loss: 4.7415 (4.6367) +2023-04-04,03:32:02 | INFO | Train Epoch: 0 [2201664/2339328 (94%)] Data (t): 0.034 Batch (t): 0.908, 70.7523/s LR: 0.000000 Logit Scale: 98.074 Contrastive_loss: 0.044463 (0.11395) Caption_loss: 4.1670 (4.5215) Loss: 4.2114 (4.6355) +2023-04-04,03:33:33 | INFO | Train Epoch: 0 [2208064/2339328 (94%)] Data (t): 0.034 Batch (t): 0.911, 70.0392/s LR: 0.000000 Logit Scale: 98.074 Contrastive_loss: 0.16111 (0.11408) Caption_loss: 4.7575 (4.5222) Loss: 4.9186 (4.6363) +2023-04-04,03:35:04 | INFO | Train Epoch: 0 [2214464/2339328 (95%)] Data (t): 0.034 Batch (t): 0.910, 70.6789/s LR: 0.000000 Logit Scale: 98.074 Contrastive_loss: 0.11664 (0.11409) Caption_loss: 4.7149 (4.5228) Loss: 4.8316 (4.6369) +2023-04-04,03:36:35 | INFO | Train Epoch: 0 [2220864/2339328 (95%)] Data (t): 0.034 Batch (t): 0.910, 70.3090/s LR: 0.000000 Logit Scale: 98.074 Contrastive_loss: 0.12520 (0.11412) Caption_loss: 4.7948 (4.5235) Loss: 4.9200 (4.6377) +2023-04-04,03:38:06 | INFO | Train Epoch: 0 [2227264/2339328 (95%)] Data (t): 0.034 Batch (t): 0.917, 63.9789/s LR: 0.000000 Logit Scale: 98.074 Contrastive_loss: 0.11409 (0.11412) Caption_loss: 3.6078 (4.5209) Loss: 3.7219 (4.6350) +2023-04-04,03:39:37 | INFO | Train Epoch: 0 [2233664/2339328 (95%)] Data (t): 0.035 Batch (t): 0.909, 70.7117/s LR: 0.000000 Logit Scale: 98.074 Contrastive_loss: 0.090358 (0.11405) Caption_loss: 4.1302 (4.5198) Loss: 4.2206 (4.6339) +2023-04-04,03:41:09 | INFO | Train Epoch: 0 [2240064/2339328 (96%)] Data (t): 0.035 Batch (t): 0.919, 70.1771/s LR: 0.000000 Logit Scale: 98.074 Contrastive_loss: 0.046435 (0.11386) Caption_loss: 3.9494 (4.5182) Loss: 3.9958 (4.6320) +2023-04-04,03:42:40 | INFO | Train Epoch: 0 [2246464/2339328 (96%)] Data (t): 0.034 Batch (t): 0.910, 70.4220/s LR: 0.000000 Logit Scale: 98.074 Contrastive_loss: 0.011341 (0.11357) Caption_loss: 4.6724 (4.5186) Loss: 4.6837 (4.6322) +2023-04-04,03:44:11 | INFO | Train Epoch: 0 [2252864/2339328 (96%)] Data (t): 0.034 Batch (t): 0.913, 70.2106/s LR: 0.000000 Logit Scale: 98.074 Contrastive_loss: 0.033071 (0.11334) Caption_loss: 3.2168 (4.5149) Loss: 3.2498 (4.6283) +2023-04-04,03:45:43 | INFO | Train Epoch: 0 [2259264/2339328 (97%)] Data (t): 0.034 Batch (t): 0.912, 70.0629/s LR: 0.000000 Logit Scale: 98.074 Contrastive_loss: 0.051205 (0.11317) Caption_loss: 4.1754 (4.5140) Loss: 4.2266 (4.6271) +2023-04-04,03:47:13 | INFO | Train Epoch: 0 [2265664/2339328 (97%)] Data (t): 0.034 Batch (t): 0.908, 70.0094/s LR: 0.000000 Logit Scale: 98.074 Contrastive_loss: 0.11932 (0.11318) Caption_loss: 3.3697 (4.5107) Loss: 3.4890 (4.6239) +2023-04-04,03:48:45 | INFO | Train Epoch: 0 [2272064/2339328 (97%)] Data (t): 0.034 Batch (t): 0.911, 70.3888/s LR: 0.000000 Logit Scale: 98.074 Contrastive_loss: 0.15883 (0.11331) Caption_loss: 3.3842 (4.5076) Loss: 3.5430 (4.6209) +2023-04-04,03:50:16 | INFO | Train Epoch: 0 [2278464/2339328 (97%)] Data (t): 0.034 Batch (t): 0.911, 66.0191/s LR: 0.000000 Logit Scale: 98.074 Contrastive_loss: 0.054559 (0.11315) Caption_loss: 5.3559 (4.5100) Loss: 5.4105 (4.6231) +2023-04-04,03:51:47 | INFO | Train Epoch: 0 [2284864/2339328 (98%)] Data (t): 0.034 Batch (t): 0.914, 70.0395/s LR: 0.000000 Logit Scale: 98.074 Contrastive_loss: 0.066243 (0.11302) Caption_loss: 3.7199 (4.5078) Loss: 3.7861 (4.6208) +2023-04-04,03:53:18 | INFO | Train Epoch: 0 [2291264/2339328 (98%)] Data (t): 0.034 Batch (t): 0.913, 69.6099/s LR: 0.000000 Logit Scale: 98.074 Contrastive_loss: 0.066464 (0.11289) Caption_loss: 4.1484 (4.5068) Loss: 4.2149 (4.6196) +2023-04-04,03:54:49 | INFO | Train Epoch: 0 [2297664/2339328 (98%)] Data (t): 0.034 Batch (t): 0.911, 69.0849/s LR: 0.000000 Logit Scale: 98.074 Contrastive_loss: 0.10446 (0.11286) Caption_loss: 4.5298 (4.5068) Loss: 4.6343 (4.6197) +2023-04-04,03:56:21 | INFO | Train Epoch: 0 [2304064/2339328 (98%)] Data (t): 0.034 Batch (t): 0.914, 68.8982/s LR: 0.000000 Logit Scale: 98.074 Contrastive_loss: 0.036937 (0.11265) Caption_loss: 4.8067 (4.5076) Loss: 4.8437 (4.6203) +2023-04-04,03:57:52 | INFO | Train Epoch: 0 [2310464/2339328 (99%)] Data (t): 0.034 Batch (t): 0.912, 69.4659/s LR: 0.000000 Logit Scale: 98.074 Contrastive_loss: 0.12441 (0.11268) Caption_loss: 5.8798 (4.5114) Loss: 6.0042 (4.6241) +2023-04-04,03:59:23 | INFO | Train Epoch: 0 [2316864/2339328 (99%)] Data (t): 0.034 Batch (t): 0.911, 70.0631/s LR: 0.000000 Logit Scale: 98.074 Contrastive_loss: 0.0051861 (0.11239) Caption_loss: 4.5428 (4.5115) Loss: 4.5479 (4.6239) +2023-04-04,04:00:54 | INFO | Train Epoch: 0 [2323264/2339328 (99%)] Data (t): 0.034 Batch (t): 0.910, 70.0140/s LR: 0.000000 Logit Scale: 98.074 Contrastive_loss: 0.087878 (0.11232) Caption_loss: 5.2815 (4.5136) Loss: 5.3694 (4.6260) +2023-04-04,04:02:25 | INFO | Train Epoch: 0 [2329664/2339328 (100%)] Data (t): 0.034 Batch (t): 0.909, 70.0141/s LR: 0.000000 Logit Scale: 98.074 Contrastive_loss: 0.098488 (0.11228) Caption_loss: 4.6305 (4.5140) Loss: 4.7290 (4.6262) +2023-04-04,04:03:56 | INFO | Train Epoch: 0 [2336064/2339328 (100%)] Data (t): 0.034 Batch (t): 0.910, 69.6833/s LR: 0.000000 Logit Scale: 98.074 Contrastive_loss: 0.080947 (0.11220) Caption_loss: 4.2694 (4.5133) Loss: 4.3504 (4.6255) +2023-04-04,04:04:43 | INFO | Train Epoch: 0 [2339328/2339328 (100%)] Data (t): 0.035 Batch (t): 0.925, 69.2720/s LR: 0.000000 Logit Scale: 98.074 Contrastive_loss: 0.12045 (0.11222) Caption_loss: 4.0942 (4.5121) Loss: 4.2146 (4.6244)