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uwk-cegov
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information_obligation_classifier

Text Classification
German
legal text
information obligation
Model card Files Community
LThurnay commited on
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  1. dev.tsv +0 -0
  2. final-model.pt +3 -0
  3. loss.tsv +41 -0
  4. parameters.txt +3 -0
  5. test.tsv +0 -0
  6. training.log +778 -0
dev.tsv ADDED
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+ EPOCH TIMESTAMP LEARNING_RATE TRAIN_LOSS DEV_LOSS DEV_PRECISION DEV_RECALL DEV_F1 DEV_ACCURACY
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parameters.txt ADDED
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+ embedding: dbmdz/bert-base-german-cased
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+ mini_batch: 16
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+ optimizer: <class 'torch.optim.adamw.AdamW'>
test.tsv ADDED
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training.log ADDED
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+ 2024-06-23 23:29:26,936 ----------------------------------------------------------------------------------------------------
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+ 2024-06-23 23:29:26,936 Model: "TextClassifier(
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+ (embeddings): TransformerDocumentEmbeddings(
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+ (model): BertModel(
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+ (embeddings): BertEmbeddings(
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+ (word_embeddings): Embedding(31103, 768)
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+ (position_embeddings): Embedding(512, 768)
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+ (token_type_embeddings): Embedding(2, 768)
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+ (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
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+ (dropout): Dropout(p=0.1, inplace=False)
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+ )
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+ (encoder): BertEncoder(
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+ (layer): ModuleList(
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+ (0-11): 12 x BertLayer(
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+ (attention): BertAttention(
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+ (self): BertSelfAttention(
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+ (query): Linear(in_features=768, out_features=768, bias=True)
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+ (key): Linear(in_features=768, out_features=768, bias=True)
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+ (value): Linear(in_features=768, out_features=768, bias=True)
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+ (dropout): Dropout(p=0.1, inplace=False)
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+ )
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+ (output): BertSelfOutput(
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+ (dense): Linear(in_features=768, out_features=768, bias=True)
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+ (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
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+ (dropout): Dropout(p=0.1, inplace=False)
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+ )
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+ )
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+ (intermediate): BertIntermediate(
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+ (dense): Linear(in_features=768, out_features=3072, bias=True)
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+ (intermediate_act_fn): GELUActivation()
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+ )
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+ (output): BertOutput(
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+ (dense): Linear(in_features=3072, out_features=768, bias=True)
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+ (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
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+ (dropout): Dropout(p=0.1, inplace=False)
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+ )
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+ )
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+ )
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+ )
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+ (pooler): BertPooler(
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+ (dense): Linear(in_features=768, out_features=768, bias=True)
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+ (activation): Tanh()
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+ )
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+ )
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+ )
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+ (decoder): Linear(in_features=768, out_features=2, bias=True)
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+ (dropout): Dropout(p=0.0, inplace=False)
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+ (locked_dropout): LockedDropout(p=0.0)
49
+ (word_dropout): WordDropout(p=0.0)
50
+ (loss_function): CrossEntropyLoss()
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+ (weights): None
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+ (weight_tensor) None
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+ )"
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+ 2024-06-23 23:29:26,937 ----------------------------------------------------------------------------------------------------
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+ 2024-06-23 23:29:26,937 Corpus: 617 train + 76 dev + 79 test sentences
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+ 2024-06-23 23:29:26,937 ----------------------------------------------------------------------------------------------------
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+ 2024-06-23 23:29:26,937 Train: 617 sentences
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+ 2024-06-23 23:29:26,937 (train_with_dev=False, train_with_test=False)
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+ 2024-06-23 23:29:26,937 ----------------------------------------------------------------------------------------------------
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+ 2024-06-23 23:29:26,937 Training Params:
61
+ 2024-06-23 23:29:26,937 - learning_rate: "5e-05"
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+ 2024-06-23 23:29:26,937 - mini_batch_size: "16"
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+ 2024-06-23 23:29:26,937 - max_epochs: "40"
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+ 2024-06-23 23:29:26,937 - shuffle: "True"
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+ 2024-06-23 23:29:26,937 ----------------------------------------------------------------------------------------------------
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+ 2024-06-23 23:29:26,937 Plugins:
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+ 2024-06-23 23:29:26,937 - TensorboardLogger
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+ 2024-06-23 23:29:26,937 - LinearScheduler | warmup_fraction: '0.1'
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+ 2024-06-23 23:29:26,937 ----------------------------------------------------------------------------------------------------
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+ 2024-06-23 23:29:26,937 Final evaluation on model after last epoch (final-model.pt)
71
+ 2024-06-23 23:29:26,937 - metric: "('micro avg', 'f1-score')"
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+ 2024-06-23 23:29:26,937 ----------------------------------------------------------------------------------------------------
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+ 2024-06-23 23:29:26,937 Computation:
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+ 2024-06-23 23:29:26,937 - compute on device: cuda:0
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+ 2024-06-23 23:29:26,937 - embedding storage: none
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+ 2024-06-23 23:29:26,937 ----------------------------------------------------------------------------------------------------
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+ 2024-06-23 23:29:26,937 Model training base path: "/data/ivdb/models/2024-06-23-232925"
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+ 2024-06-23 23:29:26,937 ----------------------------------------------------------------------------------------------------
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+ 2024-06-23 23:29:26,938 ----------------------------------------------------------------------------------------------------
80
+ 2024-06-23 23:29:26,938 Logging anything other than scalars to TensorBoard is currently not supported.
81
+ 2024-06-23 23:29:33,821 epoch 1 - iter 3/39 - loss 0.93455690 - time (sec): 6.88 - samples/sec: 6.97 - lr: 0.000001 - momentum: 0.000000
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+ 2024-06-23 23:29:38,509 epoch 1 - iter 6/39 - loss 0.92026678 - time (sec): 11.57 - samples/sec: 8.30 - lr: 0.000002 - momentum: 0.000000
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+ 2024-06-23 23:29:44,896 epoch 1 - iter 9/39 - loss 0.87347190 - time (sec): 17.96 - samples/sec: 8.02 - lr: 0.000003 - momentum: 0.000000
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+ 2024-06-23 23:29:50,040 epoch 1 - iter 12/39 - loss 0.83988379 - time (sec): 23.10 - samples/sec: 8.31 - lr: 0.000003 - momentum: 0.000000
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+ 2024-06-23 23:29:55,462 epoch 1 - iter 15/39 - loss 0.79978426 - time (sec): 28.52 - samples/sec: 8.41 - lr: 0.000004 - momentum: 0.000000
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+ 2024-06-23 23:30:00,322 epoch 1 - iter 18/39 - loss 0.76008364 - time (sec): 33.38 - samples/sec: 8.63 - lr: 0.000005 - momentum: 0.000000
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+ 2024-06-23 23:30:04,805 epoch 1 - iter 21/39 - loss 0.73865537 - time (sec): 37.87 - samples/sec: 8.87 - lr: 0.000006 - momentum: 0.000000
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+ 2024-06-23 23:30:12,256 epoch 1 - iter 24/39 - loss 0.73148594 - time (sec): 45.32 - samples/sec: 8.47 - lr: 0.000007 - momentum: 0.000000
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+ 2024-06-23 23:30:17,851 epoch 1 - iter 27/39 - loss 0.71394623 - time (sec): 50.91 - samples/sec: 8.49 - lr: 0.000008 - momentum: 0.000000
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+ 2024-06-23 23:30:22,326 epoch 1 - iter 30/39 - loss 0.70852675 - time (sec): 55.39 - samples/sec: 8.67 - lr: 0.000009 - momentum: 0.000000
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+ 2024-06-23 23:30:28,221 epoch 1 - iter 33/39 - loss 0.67715247 - time (sec): 61.28 - samples/sec: 8.62 - lr: 0.000010 - momentum: 0.000000
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+ 2024-06-23 23:30:34,225 epoch 1 - iter 36/39 - loss 0.65612338 - time (sec): 67.29 - samples/sec: 8.56 - lr: 0.000011 - momentum: 0.000000
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+ 2024-06-23 23:30:37,993 epoch 1 - iter 39/39 - loss 0.65546145 - time (sec): 71.05 - samples/sec: 8.68 - lr: 0.000012 - momentum: 0.000000
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+ 2024-06-23 23:30:37,993 ----------------------------------------------------------------------------------------------------
95
+ 2024-06-23 23:30:37,993 EPOCH 1 done: loss 0.6555 - lr: 0.000012
96
+ 2024-06-23 23:30:42,796 DEV : loss 0.5017538666725159 - f1-score (micro avg) 0.75
97
+ 2024-06-23 23:30:44,501 ----------------------------------------------------------------------------------------------------
98
+ 2024-06-23 23:30:49,514 epoch 2 - iter 3/39 - loss 0.62652248 - time (sec): 5.01 - samples/sec: 9.58 - lr: 0.000013 - momentum: 0.000000
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+ 2024-06-23 23:30:54,304 epoch 2 - iter 6/39 - loss 0.55089944 - time (sec): 9.80 - samples/sec: 9.79 - lr: 0.000014 - momentum: 0.000000
100
+ 2024-06-23 23:30:58,877 epoch 2 - iter 9/39 - loss 0.51546845 - time (sec): 14.37 - samples/sec: 10.02 - lr: 0.000015 - momentum: 0.000000
101
+ 2024-06-23 23:31:05,015 epoch 2 - iter 12/39 - loss 0.48959405 - time (sec): 20.51 - samples/sec: 9.36 - lr: 0.000016 - momentum: 0.000000
102
+ 2024-06-23 23:31:12,604 epoch 2 - iter 15/39 - loss 0.47114836 - time (sec): 28.10 - samples/sec: 8.54 - lr: 0.000017 - momentum: 0.000000
103
+ 2024-06-23 23:31:18,844 epoch 2 - iter 18/39 - loss 0.44175672 - time (sec): 34.34 - samples/sec: 8.39 - lr: 0.000018 - momentum: 0.000000
104
+ 2024-06-23 23:31:23,623 epoch 2 - iter 21/39 - loss 0.44914545 - time (sec): 39.12 - samples/sec: 8.59 - lr: 0.000019 - momentum: 0.000000
105
+ 2024-06-23 23:31:29,386 epoch 2 - iter 24/39 - loss 0.43354483 - time (sec): 44.88 - samples/sec: 8.56 - lr: 0.000020 - momentum: 0.000000
106
+ 2024-06-23 23:31:34,085 epoch 2 - iter 27/39 - loss 0.44229239 - time (sec): 49.58 - samples/sec: 8.71 - lr: 0.000021 - momentum: 0.000000
107
+ 2024-06-23 23:31:39,464 epoch 2 - iter 30/39 - loss 0.42628914 - time (sec): 54.96 - samples/sec: 8.73 - lr: 0.000022 - momentum: 0.000000
108
+ 2024-06-23 23:31:46,064 epoch 2 - iter 33/39 - loss 0.41278999 - time (sec): 61.56 - samples/sec: 8.58 - lr: 0.000022 - momentum: 0.000000
109
+ 2024-06-23 23:31:50,776 epoch 2 - iter 36/39 - loss 0.41018313 - time (sec): 66.27 - samples/sec: 8.69 - lr: 0.000023 - momentum: 0.000000
110
+ 2024-06-23 23:31:54,808 epoch 2 - iter 39/39 - loss 0.40660896 - time (sec): 70.31 - samples/sec: 8.78 - lr: 0.000024 - momentum: 0.000000
111
+ 2024-06-23 23:31:54,809 ----------------------------------------------------------------------------------------------------
112
+ 2024-06-23 23:31:54,809 EPOCH 2 done: loss 0.4066 - lr: 0.000024
113
+ 2024-06-23 23:31:59,535 DEV : loss 0.3630148768424988 - f1-score (micro avg) 0.8684
114
+ 2024-06-23 23:32:01,243 ----------------------------------------------------------------------------------------------------
115
+ 2024-06-23 23:32:06,820 epoch 3 - iter 3/39 - loss 0.18468438 - time (sec): 5.58 - samples/sec: 8.61 - lr: 0.000025 - momentum: 0.000000
116
+ 2024-06-23 23:32:12,275 epoch 3 - iter 6/39 - loss 0.27910875 - time (sec): 11.03 - samples/sec: 8.70 - lr: 0.000026 - momentum: 0.000000
117
+ 2024-06-23 23:32:17,083 epoch 3 - iter 9/39 - loss 0.32698032 - time (sec): 15.84 - samples/sec: 9.09 - lr: 0.000027 - momentum: 0.000000
118
+ 2024-06-23 23:32:24,993 epoch 3 - iter 12/39 - loss 0.33958591 - time (sec): 23.75 - samples/sec: 8.08 - lr: 0.000028 - momentum: 0.000000
119
+ 2024-06-23 23:32:30,907 epoch 3 - iter 15/39 - loss 0.32360529 - time (sec): 29.66 - samples/sec: 8.09 - lr: 0.000029 - momentum: 0.000000
120
+ 2024-06-23 23:32:35,708 epoch 3 - iter 18/39 - loss 0.31533587 - time (sec): 34.46 - samples/sec: 8.36 - lr: 0.000030 - momentum: 0.000000
121
+ 2024-06-23 23:32:40,620 epoch 3 - iter 21/39 - loss 0.30045377 - time (sec): 39.38 - samples/sec: 8.53 - lr: 0.000031 - momentum: 0.000000
122
+ 2024-06-23 23:32:45,487 epoch 3 - iter 24/39 - loss 0.28366955 - time (sec): 44.24 - samples/sec: 8.68 - lr: 0.000032 - momentum: 0.000000
123
+ 2024-06-23 23:32:54,051 epoch 3 - iter 27/39 - loss 0.28988732 - time (sec): 52.81 - samples/sec: 8.18 - lr: 0.000033 - momentum: 0.000000
124
+ 2024-06-23 23:32:58,828 epoch 3 - iter 30/39 - loss 0.27671992 - time (sec): 57.58 - samples/sec: 8.34 - lr: 0.000034 - momentum: 0.000000
125
+ 2024-06-23 23:33:03,728 epoch 3 - iter 33/39 - loss 0.28976736 - time (sec): 62.48 - samples/sec: 8.45 - lr: 0.000035 - momentum: 0.000000
126
+ 2024-06-23 23:33:08,339 epoch 3 - iter 36/39 - loss 0.27887381 - time (sec): 67.09 - samples/sec: 8.58 - lr: 0.000036 - momentum: 0.000000
127
+ 2024-06-23 23:33:12,332 epoch 3 - iter 39/39 - loss 0.28789787 - time (sec): 71.09 - samples/sec: 8.68 - lr: 0.000037 - momentum: 0.000000
128
+ 2024-06-23 23:33:12,332 ----------------------------------------------------------------------------------------------------
129
+ 2024-06-23 23:33:12,332 EPOCH 3 done: loss 0.2879 - lr: 0.000037
130
+ 2024-06-23 23:33:17,172 DEV : loss 0.33866241574287415 - f1-score (micro avg) 0.8947
131
+ 2024-06-23 23:33:18,778 ----------------------------------------------------------------------------------------------------
132
+ 2024-06-23 23:33:27,476 epoch 4 - iter 3/39 - loss 0.06723633 - time (sec): 8.70 - samples/sec: 5.52 - lr: 0.000038 - momentum: 0.000000
133
+ 2024-06-23 23:33:32,117 epoch 4 - iter 6/39 - loss 0.14415476 - time (sec): 13.34 - samples/sec: 7.20 - lr: 0.000039 - momentum: 0.000000
134
+ 2024-06-23 23:33:37,619 epoch 4 - iter 9/39 - loss 0.13159802 - time (sec): 18.84 - samples/sec: 7.64 - lr: 0.000040 - momentum: 0.000000
135
+ 2024-06-23 23:33:42,442 epoch 4 - iter 12/39 - loss 0.12807673 - time (sec): 23.66 - samples/sec: 8.11 - lr: 0.000041 - momentum: 0.000000
136
+ 2024-06-23 23:33:47,589 epoch 4 - iter 15/39 - loss 0.11112227 - time (sec): 28.81 - samples/sec: 8.33 - lr: 0.000041 - momentum: 0.000000
137
+ 2024-06-23 23:33:52,400 epoch 4 - iter 18/39 - loss 0.10901718 - time (sec): 33.62 - samples/sec: 8.57 - lr: 0.000042 - momentum: 0.000000
138
+ 2024-06-23 23:33:57,236 epoch 4 - iter 21/39 - loss 0.09612736 - time (sec): 38.46 - samples/sec: 8.74 - lr: 0.000043 - momentum: 0.000000
139
+ 2024-06-23 23:34:02,045 epoch 4 - iter 24/39 - loss 0.10819060 - time (sec): 43.27 - samples/sec: 8.88 - lr: 0.000044 - momentum: 0.000000
140
+ 2024-06-23 23:34:07,428 epoch 4 - iter 27/39 - loss 0.13555085 - time (sec): 48.65 - samples/sec: 8.88 - lr: 0.000045 - momentum: 0.000000
141
+ 2024-06-23 23:34:12,240 epoch 4 - iter 30/39 - loss 0.15823287 - time (sec): 53.46 - samples/sec: 8.98 - lr: 0.000046 - momentum: 0.000000
142
+ 2024-06-23 23:34:17,046 epoch 4 - iter 33/39 - loss 0.19133172 - time (sec): 58.27 - samples/sec: 9.06 - lr: 0.000047 - momentum: 0.000000
143
+ 2024-06-23 23:34:24,735 epoch 4 - iter 36/39 - loss 0.18381271 - time (sec): 65.96 - samples/sec: 8.73 - lr: 0.000048 - momentum: 0.000000
144
+ 2024-06-23 23:34:30,353 epoch 4 - iter 39/39 - loss 0.19017995 - time (sec): 71.57 - samples/sec: 8.62 - lr: 0.000049 - momentum: 0.000000
145
+ 2024-06-23 23:34:30,354 ----------------------------------------------------------------------------------------------------
146
+ 2024-06-23 23:34:30,354 EPOCH 4 done: loss 0.1902 - lr: 0.000049
147
+ 2024-06-23 23:34:35,244 DEV : loss 0.5190975069999695 - f1-score (micro avg) 0.8684
148
+ 2024-06-23 23:34:36,843 ----------------------------------------------------------------------------------------------------
149
+ 2024-06-23 23:34:41,736 epoch 5 - iter 3/39 - loss 0.12455761 - time (sec): 4.89 - samples/sec: 9.81 - lr: 0.000050 - momentum: 0.000000
150
+ 2024-06-23 23:34:46,475 epoch 5 - iter 6/39 - loss 0.13643145 - time (sec): 9.63 - samples/sec: 9.97 - lr: 0.000050 - momentum: 0.000000
151
+ 2024-06-23 23:34:52,693 epoch 5 - iter 9/39 - loss 0.16813415 - time (sec): 15.85 - samples/sec: 9.09 - lr: 0.000050 - momentum: 0.000000
152
+ 2024-06-23 23:34:57,798 epoch 5 - iter 12/39 - loss 0.22500083 - time (sec): 20.95 - samples/sec: 9.16 - lr: 0.000050 - momentum: 0.000000
153
+ 2024-06-23 23:35:05,245 epoch 5 - iter 15/39 - loss 0.18959679 - time (sec): 28.40 - samples/sec: 8.45 - lr: 0.000050 - momentum: 0.000000
154
+ 2024-06-23 23:35:11,295 epoch 5 - iter 18/39 - loss 0.22634660 - time (sec): 34.45 - samples/sec: 8.36 - lr: 0.000049 - momentum: 0.000000
155
+ 2024-06-23 23:35:17,338 epoch 5 - iter 21/39 - loss 0.21195548 - time (sec): 40.49 - samples/sec: 8.30 - lr: 0.000049 - momentum: 0.000000
156
+ 2024-06-23 23:35:22,368 epoch 5 - iter 24/39 - loss 0.24165446 - time (sec): 45.52 - samples/sec: 8.44 - lr: 0.000049 - momentum: 0.000000
157
+ 2024-06-23 23:35:28,986 epoch 5 - iter 27/39 - loss 0.34555561 - time (sec): 52.14 - samples/sec: 8.29 - lr: 0.000049 - momentum: 0.000000
158
+ 2024-06-23 23:35:34,569 epoch 5 - iter 30/39 - loss 0.32555066 - time (sec): 57.72 - samples/sec: 8.32 - lr: 0.000049 - momentum: 0.000000
159
+ 2024-06-23 23:35:39,185 epoch 5 - iter 33/39 - loss 0.35673888 - time (sec): 62.34 - samples/sec: 8.47 - lr: 0.000049 - momentum: 0.000000
160
+ 2024-06-23 23:35:44,542 epoch 5 - iter 36/39 - loss 0.34086972 - time (sec): 67.70 - samples/sec: 8.51 - lr: 0.000049 - momentum: 0.000000
161
+ 2024-06-23 23:35:48,680 epoch 5 - iter 39/39 - loss 0.33476651 - time (sec): 71.84 - samples/sec: 8.59 - lr: 0.000049 - momentum: 0.000000
162
+ 2024-06-23 23:35:48,681 ----------------------------------------------------------------------------------------------------
163
+ 2024-06-23 23:35:48,681 EPOCH 5 done: loss 0.3348 - lr: 0.000049
164
+ 2024-06-23 23:35:53,453 DEV : loss 0.6392198204994202 - f1-score (micro avg) 0.8816
165
+ 2024-06-23 23:35:55,052 ----------------------------------------------------------------------------------------------------
166
+ 2024-06-23 23:36:00,306 epoch 6 - iter 3/39 - loss 0.10281337 - time (sec): 5.25 - samples/sec: 9.14 - lr: 0.000049 - momentum: 0.000000
167
+ 2024-06-23 23:36:05,140 epoch 6 - iter 6/39 - loss 0.11683190 - time (sec): 10.09 - samples/sec: 9.52 - lr: 0.000049 - momentum: 0.000000
168
+ 2024-06-23 23:36:11,661 epoch 6 - iter 9/39 - loss 0.12543468 - time (sec): 16.61 - samples/sec: 8.67 - lr: 0.000048 - momentum: 0.000000
169
+ 2024-06-23 23:36:16,538 epoch 6 - iter 12/39 - loss 0.24078707 - time (sec): 21.48 - samples/sec: 8.94 - lr: 0.000048 - momentum: 0.000000
170
+ 2024-06-23 23:36:21,279 epoch 6 - iter 15/39 - loss 0.19658959 - time (sec): 26.23 - samples/sec: 9.15 - lr: 0.000048 - momentum: 0.000000
171
+ 2024-06-23 23:36:28,391 epoch 6 - iter 18/39 - loss 0.16910445 - time (sec): 33.34 - samples/sec: 8.64 - lr: 0.000048 - momentum: 0.000000
172
+ 2024-06-23 23:36:33,712 epoch 6 - iter 21/39 - loss 0.14931677 - time (sec): 38.66 - samples/sec: 8.69 - lr: 0.000048 - momentum: 0.000000
173
+ 2024-06-23 23:36:38,940 epoch 6 - iter 24/39 - loss 0.13100674 - time (sec): 43.89 - samples/sec: 8.75 - lr: 0.000048 - momentum: 0.000000
174
+ 2024-06-23 23:36:45,565 epoch 6 - iter 27/39 - loss 0.13358956 - time (sec): 50.51 - samples/sec: 8.55 - lr: 0.000048 - momentum: 0.000000
175
+ 2024-06-23 23:36:52,734 epoch 6 - iter 30/39 - loss 0.12239488 - time (sec): 57.68 - samples/sec: 8.32 - lr: 0.000048 - momentum: 0.000000
176
+ 2024-06-23 23:36:57,571 epoch 6 - iter 33/39 - loss 0.11163022 - time (sec): 62.52 - samples/sec: 8.45 - lr: 0.000048 - momentum: 0.000000
177
+ 2024-06-23 23:37:03,075 epoch 6 - iter 36/39 - loss 0.10362160 - time (sec): 68.02 - samples/sec: 8.47 - lr: 0.000047 - momentum: 0.000000
178
+ 2024-06-23 23:37:07,212 epoch 6 - iter 39/39 - loss 0.09678627 - time (sec): 72.16 - samples/sec: 8.55 - lr: 0.000047 - momentum: 0.000000
179
+ 2024-06-23 23:37:07,213 ----------------------------------------------------------------------------------------------------
180
+ 2024-06-23 23:37:07,213 EPOCH 6 done: loss 0.0968 - lr: 0.000047
181
+ 2024-06-23 23:37:12,022 DEV : loss 1.1822508573532104 - f1-score (micro avg) 0.8421
182
+ 2024-06-23 23:37:13,734 ----------------------------------------------------------------------------------------------------
183
+ 2024-06-23 23:37:19,211 epoch 7 - iter 3/39 - loss 0.00367758 - time (sec): 5.48 - samples/sec: 8.77 - lr: 0.000047 - momentum: 0.000000
184
+ 2024-06-23 23:37:23,835 epoch 7 - iter 6/39 - loss 0.07268900 - time (sec): 10.10 - samples/sec: 9.51 - lr: 0.000047 - momentum: 0.000000
185
+ 2024-06-23 23:37:30,291 epoch 7 - iter 9/39 - loss 0.10109780 - time (sec): 16.56 - samples/sec: 8.70 - lr: 0.000047 - momentum: 0.000000
186
+ 2024-06-23 23:37:36,792 epoch 7 - iter 12/39 - loss 0.07664083 - time (sec): 23.06 - samples/sec: 8.33 - lr: 0.000047 - momentum: 0.000000
187
+ 2024-06-23 23:37:42,111 epoch 7 - iter 15/39 - loss 0.07984787 - time (sec): 28.38 - samples/sec: 8.46 - lr: 0.000047 - momentum: 0.000000
188
+ 2024-06-23 23:37:48,029 epoch 7 - iter 18/39 - loss 0.06770204 - time (sec): 34.29 - samples/sec: 8.40 - lr: 0.000047 - momentum: 0.000000
189
+ 2024-06-23 23:37:53,055 epoch 7 - iter 21/39 - loss 0.06779089 - time (sec): 39.32 - samples/sec: 8.55 - lr: 0.000047 - momentum: 0.000000
190
+ 2024-06-23 23:37:59,410 epoch 7 - iter 24/39 - loss 0.06405825 - time (sec): 45.67 - samples/sec: 8.41 - lr: 0.000047 - momentum: 0.000000
191
+ 2024-06-23 23:38:06,673 epoch 7 - iter 27/39 - loss 0.05694537 - time (sec): 52.94 - samples/sec: 8.16 - lr: 0.000046 - momentum: 0.000000
192
+ 2024-06-23 23:38:11,348 epoch 7 - iter 30/39 - loss 0.05323722 - time (sec): 57.61 - samples/sec: 8.33 - lr: 0.000046 - momentum: 0.000000
193
+ 2024-06-23 23:38:17,251 epoch 7 - iter 33/39 - loss 0.06067778 - time (sec): 63.52 - samples/sec: 8.31 - lr: 0.000046 - momentum: 0.000000
194
+ 2024-06-23 23:38:21,919 epoch 7 - iter 36/39 - loss 0.07111521 - time (sec): 68.18 - samples/sec: 8.45 - lr: 0.000046 - momentum: 0.000000
195
+ 2024-06-23 23:38:25,974 epoch 7 - iter 39/39 - loss 0.07664184 - time (sec): 72.24 - samples/sec: 8.54 - lr: 0.000046 - momentum: 0.000000
196
+ 2024-06-23 23:38:25,974 ----------------------------------------------------------------------------------------------------
197
+ 2024-06-23 23:38:25,974 EPOCH 7 done: loss 0.0766 - lr: 0.000046
198
+ 2024-06-23 23:38:30,760 DEV : loss 1.004543662071228 - f1-score (micro avg) 0.8684
199
+ 2024-06-23 23:38:32,359 ----------------------------------------------------------------------------------------------------
200
+ 2024-06-23 23:38:38,357 epoch 8 - iter 3/39 - loss 0.00009458 - time (sec): 6.00 - samples/sec: 8.00 - lr: 0.000046 - momentum: 0.000000
201
+ 2024-06-23 23:38:44,572 epoch 8 - iter 6/39 - loss 0.01349367 - time (sec): 12.21 - samples/sec: 7.86 - lr: 0.000046 - momentum: 0.000000
202
+ 2024-06-23 23:38:49,788 epoch 8 - iter 9/39 - loss 0.06544811 - time (sec): 17.43 - samples/sec: 8.26 - lr: 0.000046 - momentum: 0.000000
203
+ 2024-06-23 23:38:55,355 epoch 8 - iter 12/39 - loss 0.05148862 - time (sec): 23.00 - samples/sec: 8.35 - lr: 0.000046 - momentum: 0.000000
204
+ 2024-06-23 23:39:00,535 epoch 8 - iter 15/39 - loss 0.04555394 - time (sec): 28.17 - samples/sec: 8.52 - lr: 0.000045 - momentum: 0.000000
205
+ 2024-06-23 23:39:05,299 epoch 8 - iter 18/39 - loss 0.03797210 - time (sec): 32.94 - samples/sec: 8.74 - lr: 0.000045 - momentum: 0.000000
206
+ 2024-06-23 23:39:10,372 epoch 8 - iter 21/39 - loss 0.03290582 - time (sec): 38.01 - samples/sec: 8.84 - lr: 0.000045 - momentum: 0.000000
207
+ 2024-06-23 23:39:15,209 epoch 8 - iter 24/39 - loss 0.02905090 - time (sec): 42.85 - samples/sec: 8.96 - lr: 0.000045 - momentum: 0.000000
208
+ 2024-06-23 23:39:20,127 epoch 8 - iter 27/39 - loss 0.03753662 - time (sec): 47.77 - samples/sec: 9.04 - lr: 0.000045 - momentum: 0.000000
209
+ 2024-06-23 23:39:25,378 epoch 8 - iter 30/39 - loss 0.04452772 - time (sec): 53.02 - samples/sec: 9.05 - lr: 0.000045 - momentum: 0.000000
210
+ 2024-06-23 23:39:31,903 epoch 8 - iter 33/39 - loss 0.04094768 - time (sec): 59.54 - samples/sec: 8.87 - lr: 0.000045 - momentum: 0.000000
211
+ 2024-06-23 23:39:38,172 epoch 8 - iter 36/39 - loss 0.04595046 - time (sec): 65.81 - samples/sec: 8.75 - lr: 0.000045 - momentum: 0.000000
212
+ 2024-06-23 23:39:44,802 epoch 8 - iter 39/39 - loss 0.04297773 - time (sec): 72.44 - samples/sec: 8.52 - lr: 0.000045 - momentum: 0.000000
213
+ 2024-06-23 23:39:44,803 ----------------------------------------------------------------------------------------------------
214
+ 2024-06-23 23:39:44,803 EPOCH 8 done: loss 0.0430 - lr: 0.000045
215
+ 2024-06-23 23:39:49,555 DEV : loss 1.2074036598205566 - f1-score (micro avg) 0.8816
216
+ 2024-06-23 23:39:51,296 ----------------------------------------------------------------------------------------------------
217
+ 2024-06-23 23:39:56,308 epoch 9 - iter 3/39 - loss 0.00068067 - time (sec): 5.01 - samples/sec: 9.58 - lr: 0.000045 - momentum: 0.000000
218
+ 2024-06-23 23:40:01,206 epoch 9 - iter 6/39 - loss 0.05288977 - time (sec): 9.91 - samples/sec: 9.69 - lr: 0.000044 - momentum: 0.000000
219
+ 2024-06-23 23:40:06,035 epoch 9 - iter 9/39 - loss 0.03526389 - time (sec): 14.74 - samples/sec: 9.77 - lr: 0.000044 - momentum: 0.000000
220
+ 2024-06-23 23:40:10,927 epoch 9 - iter 12/39 - loss 0.02645130 - time (sec): 19.63 - samples/sec: 9.78 - lr: 0.000044 - momentum: 0.000000
221
+ 2024-06-23 23:40:15,739 epoch 9 - iter 15/39 - loss 0.02270784 - time (sec): 24.44 - samples/sec: 9.82 - lr: 0.000044 - momentum: 0.000000
222
+ 2024-06-23 23:40:20,570 epoch 9 - iter 18/39 - loss 0.01892902 - time (sec): 29.27 - samples/sec: 9.84 - lr: 0.000044 - momentum: 0.000000
223
+ 2024-06-23 23:40:26,470 epoch 9 - iter 21/39 - loss 0.01907380 - time (sec): 35.17 - samples/sec: 9.55 - lr: 0.000044 - momentum: 0.000000
224
+ 2024-06-23 23:40:31,128 epoch 9 - iter 24/39 - loss 0.01669493 - time (sec): 39.83 - samples/sec: 9.64 - lr: 0.000044 - momentum: 0.000000
225
+ 2024-06-23 23:40:37,779 epoch 9 - iter 27/39 - loss 0.01488654 - time (sec): 46.48 - samples/sec: 9.29 - lr: 0.000044 - momentum: 0.000000
226
+ 2024-06-23 23:40:42,883 epoch 9 - iter 30/39 - loss 0.01339824 - time (sec): 51.59 - samples/sec: 9.30 - lr: 0.000044 - momentum: 0.000000
227
+ 2024-06-23 23:40:50,497 epoch 9 - iter 33/39 - loss 0.01220745 - time (sec): 59.20 - samples/sec: 8.92 - lr: 0.000043 - momentum: 0.000000
228
+ 2024-06-23 23:40:58,027 epoch 9 - iter 36/39 - loss 0.01119089 - time (sec): 66.73 - samples/sec: 8.63 - lr: 0.000043 - momentum: 0.000000
229
+ 2024-06-23 23:41:03,434 epoch 9 - iter 39/39 - loss 0.01044824 - time (sec): 72.14 - samples/sec: 8.55 - lr: 0.000043 - momentum: 0.000000
230
+ 2024-06-23 23:41:03,434 ----------------------------------------------------------------------------------------------------
231
+ 2024-06-23 23:41:03,434 EPOCH 9 done: loss 0.0104 - lr: 0.000043
232
+ 2024-06-23 23:41:08,234 DEV : loss 1.5907199382781982 - f1-score (micro avg) 0.8553
233
+ 2024-06-23 23:41:09,983 ----------------------------------------------------------------------------------------------------
234
+ 2024-06-23 23:41:15,388 epoch 10 - iter 3/39 - loss 0.00290251 - time (sec): 5.40 - samples/sec: 8.88 - lr: 0.000043 - momentum: 0.000000
235
+ 2024-06-23 23:41:21,479 epoch 10 - iter 6/39 - loss 0.00146658 - time (sec): 11.49 - samples/sec: 8.35 - lr: 0.000043 - momentum: 0.000000
236
+ 2024-06-23 23:41:27,839 epoch 10 - iter 9/39 - loss 0.00097796 - time (sec): 17.85 - samples/sec: 8.06 - lr: 0.000043 - momentum: 0.000000
237
+ 2024-06-23 23:41:32,785 epoch 10 - iter 12/39 - loss 0.00073999 - time (sec): 22.80 - samples/sec: 8.42 - lr: 0.000043 - momentum: 0.000000
238
+ 2024-06-23 23:41:37,473 epoch 10 - iter 15/39 - loss 0.03087843 - time (sec): 27.49 - samples/sec: 8.73 - lr: 0.000043 - momentum: 0.000000
239
+ 2024-06-23 23:41:44,778 epoch 10 - iter 18/39 - loss 0.02574302 - time (sec): 34.79 - samples/sec: 8.28 - lr: 0.000043 - momentum: 0.000000
240
+ 2024-06-23 23:41:49,889 epoch 10 - iter 21/39 - loss 0.03273100 - time (sec): 39.90 - samples/sec: 8.42 - lr: 0.000043 - momentum: 0.000000
241
+ 2024-06-23 23:41:54,878 epoch 10 - iter 24/39 - loss 0.02863986 - time (sec): 44.89 - samples/sec: 8.55 - lr: 0.000042 - momentum: 0.000000
242
+ 2024-06-23 23:41:59,604 epoch 10 - iter 27/39 - loss 0.02545767 - time (sec): 49.62 - samples/sec: 8.71 - lr: 0.000042 - momentum: 0.000000
243
+ 2024-06-23 23:42:06,010 epoch 10 - iter 30/39 - loss 0.02291905 - time (sec): 56.03 - samples/sec: 8.57 - lr: 0.000042 - momentum: 0.000000
244
+ 2024-06-23 23:42:12,656 epoch 10 - iter 33/39 - loss 0.02085801 - time (sec): 62.67 - samples/sec: 8.42 - lr: 0.000042 - momentum: 0.000000
245
+ 2024-06-23 23:42:17,732 epoch 10 - iter 36/39 - loss 0.01912121 - time (sec): 67.75 - samples/sec: 8.50 - lr: 0.000042 - momentum: 0.000000
246
+ 2024-06-23 23:42:22,158 epoch 10 - iter 39/39 - loss 0.01785281 - time (sec): 72.17 - samples/sec: 8.55 - lr: 0.000042 - momentum: 0.000000
247
+ 2024-06-23 23:42:22,158 ----------------------------------------------------------------------------------------------------
248
+ 2024-06-23 23:42:22,158 EPOCH 10 done: loss 0.0179 - lr: 0.000042
249
+ 2024-06-23 23:42:26,950 DEV : loss 1.3823747634887695 - f1-score (micro avg) 0.8553
250
+ 2024-06-23 23:42:28,656 ----------------------------------------------------------------------------------------------------
251
+ 2024-06-23 23:42:33,578 epoch 11 - iter 3/39 - loss 0.00037880 - time (sec): 4.92 - samples/sec: 9.75 - lr: 0.000042 - momentum: 0.000000
252
+ 2024-06-23 23:42:40,756 epoch 11 - iter 6/39 - loss 0.00019021 - time (sec): 12.10 - samples/sec: 7.93 - lr: 0.000042 - momentum: 0.000000
253
+ 2024-06-23 23:42:45,931 epoch 11 - iter 9/39 - loss 0.00014317 - time (sec): 17.27 - samples/sec: 8.34 - lr: 0.000042 - momentum: 0.000000
254
+ 2024-06-23 23:42:50,849 epoch 11 - iter 12/39 - loss 0.00010746 - time (sec): 22.19 - samples/sec: 8.65 - lr: 0.000041 - momentum: 0.000000
255
+ 2024-06-23 23:42:56,673 epoch 11 - iter 15/39 - loss 0.00018469 - time (sec): 28.02 - samples/sec: 8.57 - lr: 0.000041 - momentum: 0.000000
256
+ 2024-06-23 23:43:01,802 epoch 11 - iter 18/39 - loss 0.00015400 - time (sec): 33.14 - samples/sec: 8.69 - lr: 0.000041 - momentum: 0.000000
257
+ 2024-06-23 23:43:06,664 epoch 11 - iter 21/39 - loss 0.00013212 - time (sec): 38.01 - samples/sec: 8.84 - lr: 0.000041 - momentum: 0.000000
258
+ 2024-06-23 23:43:13,922 epoch 11 - iter 24/39 - loss 0.00012075 - time (sec): 45.27 - samples/sec: 8.48 - lr: 0.000041 - momentum: 0.000000
259
+ 2024-06-23 23:43:19,164 epoch 11 - iter 27/39 - loss 0.00010768 - time (sec): 50.51 - samples/sec: 8.55 - lr: 0.000041 - momentum: 0.000000
260
+ 2024-06-23 23:43:24,119 epoch 11 - iter 30/39 - loss 0.00009707 - time (sec): 55.46 - samples/sec: 8.65 - lr: 0.000041 - momentum: 0.000000
261
+ 2024-06-23 23:43:31,924 epoch 11 - iter 33/39 - loss 0.00008831 - time (sec): 63.27 - samples/sec: 8.35 - lr: 0.000041 - momentum: 0.000000
262
+ 2024-06-23 23:43:36,757 epoch 11 - iter 36/39 - loss 0.00406036 - time (sec): 68.10 - samples/sec: 8.46 - lr: 0.000041 - momentum: 0.000000
263
+ 2024-06-23 23:43:41,065 epoch 11 - iter 39/39 - loss 0.00379065 - time (sec): 72.41 - samples/sec: 8.52 - lr: 0.000041 - momentum: 0.000000
264
+ 2024-06-23 23:43:41,066 ----------------------------------------------------------------------------------------------------
265
+ 2024-06-23 23:43:41,066 EPOCH 11 done: loss 0.0038 - lr: 0.000041
266
+ 2024-06-23 23:43:45,841 DEV : loss 1.270772933959961 - f1-score (micro avg) 0.8947
267
+ 2024-06-23 23:43:47,563 ----------------------------------------------------------------------------------------------------
268
+ 2024-06-23 23:43:53,869 epoch 12 - iter 3/39 - loss 0.00000028 - time (sec): 6.30 - samples/sec: 7.61 - lr: 0.000040 - momentum: 0.000000
269
+ 2024-06-23 23:43:59,747 epoch 12 - iter 6/39 - loss 0.00000041 - time (sec): 12.18 - samples/sec: 7.88 - lr: 0.000040 - momentum: 0.000000
270
+ 2024-06-23 23:44:04,427 epoch 12 - iter 9/39 - loss 0.00830625 - time (sec): 16.86 - samples/sec: 8.54 - lr: 0.000040 - momentum: 0.000000
271
+ 2024-06-23 23:44:09,084 epoch 12 - iter 12/39 - loss 0.01907569 - time (sec): 21.52 - samples/sec: 8.92 - lr: 0.000040 - momentum: 0.000000
272
+ 2024-06-23 23:44:15,876 epoch 12 - iter 15/39 - loss 0.01526067 - time (sec): 28.31 - samples/sec: 8.48 - lr: 0.000040 - momentum: 0.000000
273
+ 2024-06-23 23:44:20,778 epoch 12 - iter 18/39 - loss 0.01340097 - time (sec): 33.21 - samples/sec: 8.67 - lr: 0.000040 - momentum: 0.000000
274
+ 2024-06-23 23:44:26,562 epoch 12 - iter 21/39 - loss 0.01148827 - time (sec): 39.00 - samples/sec: 8.62 - lr: 0.000040 - momentum: 0.000000
275
+ 2024-06-23 23:44:32,697 epoch 12 - iter 24/39 - loss 0.01005287 - time (sec): 45.13 - samples/sec: 8.51 - lr: 0.000040 - momentum: 0.000000
276
+ 2024-06-23 23:44:39,395 epoch 12 - iter 27/39 - loss 0.01038687 - time (sec): 51.83 - samples/sec: 8.33 - lr: 0.000040 - momentum: 0.000000
277
+ 2024-06-23 23:44:44,879 epoch 12 - iter 30/39 - loss 0.00934962 - time (sec): 57.31 - samples/sec: 8.37 - lr: 0.000039 - momentum: 0.000000
278
+ 2024-06-23 23:44:50,290 epoch 12 - iter 33/39 - loss 0.02547252 - time (sec): 62.73 - samples/sec: 8.42 - lr: 0.000039 - momentum: 0.000000
279
+ 2024-06-23 23:44:55,693 epoch 12 - iter 36/39 - loss 0.02335309 - time (sec): 68.13 - samples/sec: 8.45 - lr: 0.000039 - momentum: 0.000000
280
+ 2024-06-23 23:44:59,717 epoch 12 - iter 39/39 - loss 0.02180154 - time (sec): 72.15 - samples/sec: 8.55 - lr: 0.000039 - momentum: 0.000000
281
+ 2024-06-23 23:44:59,717 ----------------------------------------------------------------------------------------------------
282
+ 2024-06-23 23:44:59,717 EPOCH 12 done: loss 0.0218 - lr: 0.000039
283
+ 2024-06-23 23:45:04,519 DEV : loss 1.5972371101379395 - f1-score (micro avg) 0.8947
284
+ 2024-06-23 23:45:06,235 ----------------------------------------------------------------------------------------------------
285
+ 2024-06-23 23:45:11,210 epoch 13 - iter 3/39 - loss 0.00042464 - time (sec): 4.97 - samples/sec: 9.65 - lr: 0.000039 - momentum: 0.000000
286
+ 2024-06-23 23:45:17,832 epoch 13 - iter 6/39 - loss 0.00021239 - time (sec): 11.60 - samples/sec: 8.28 - lr: 0.000039 - momentum: 0.000000
287
+ 2024-06-23 23:45:22,558 epoch 13 - iter 9/39 - loss 0.00014175 - time (sec): 16.32 - samples/sec: 8.82 - lr: 0.000039 - momentum: 0.000000
288
+ 2024-06-23 23:45:28,624 epoch 13 - iter 12/39 - loss 0.00010819 - time (sec): 22.39 - samples/sec: 8.58 - lr: 0.000039 - momentum: 0.000000
289
+ 2024-06-23 23:45:33,423 epoch 13 - iter 15/39 - loss 0.00015041 - time (sec): 27.19 - samples/sec: 8.83 - lr: 0.000039 - momentum: 0.000000
290
+ 2024-06-23 23:45:39,621 epoch 13 - iter 18/39 - loss 0.00012895 - time (sec): 33.39 - samples/sec: 8.63 - lr: 0.000039 - momentum: 0.000000
291
+ 2024-06-23 23:45:44,578 epoch 13 - iter 21/39 - loss 0.00011055 - time (sec): 38.34 - samples/sec: 8.76 - lr: 0.000038 - momentum: 0.000000
292
+ 2024-06-23 23:45:52,329 epoch 13 - iter 24/39 - loss 0.00009680 - time (sec): 46.09 - samples/sec: 8.33 - lr: 0.000038 - momentum: 0.000000
293
+ 2024-06-23 23:45:57,404 epoch 13 - iter 27/39 - loss 0.00013552 - time (sec): 51.17 - samples/sec: 8.44 - lr: 0.000038 - momentum: 0.000000
294
+ 2024-06-23 23:46:02,364 epoch 13 - iter 30/39 - loss 0.00012256 - time (sec): 56.13 - samples/sec: 8.55 - lr: 0.000038 - momentum: 0.000000
295
+ 2024-06-23 23:46:07,919 epoch 13 - iter 33/39 - loss 0.00423856 - time (sec): 61.68 - samples/sec: 8.56 - lr: 0.000038 - momentum: 0.000000
296
+ 2024-06-23 23:46:14,279 epoch 13 - iter 36/39 - loss 0.00388536 - time (sec): 68.04 - samples/sec: 8.47 - lr: 0.000038 - momentum: 0.000000
297
+ 2024-06-23 23:46:18,481 epoch 13 - iter 39/39 - loss 0.00365058 - time (sec): 72.24 - samples/sec: 8.54 - lr: 0.000038 - momentum: 0.000000
298
+ 2024-06-23 23:46:18,481 ----------------------------------------------------------------------------------------------------
299
+ 2024-06-23 23:46:18,481 EPOCH 13 done: loss 0.0037 - lr: 0.000038
300
+ 2024-06-23 23:46:23,265 DEV : loss 1.463855504989624 - f1-score (micro avg) 0.8816
301
+ 2024-06-23 23:46:24,860 ----------------------------------------------------------------------------------------------------
302
+ 2024-06-23 23:46:30,906 epoch 14 - iter 3/39 - loss 0.00000010 - time (sec): 6.05 - samples/sec: 7.94 - lr: 0.000038 - momentum: 0.000000
303
+ 2024-06-23 23:46:36,765 epoch 14 - iter 6/39 - loss 0.00000019 - time (sec): 11.90 - samples/sec: 8.06 - lr: 0.000038 - momentum: 0.000000
304
+ 2024-06-23 23:46:43,146 epoch 14 - iter 9/39 - loss 0.00000030 - time (sec): 18.28 - samples/sec: 7.88 - lr: 0.000037 - momentum: 0.000000
305
+ 2024-06-23 23:46:47,958 epoch 14 - iter 12/39 - loss 0.00000027 - time (sec): 23.10 - samples/sec: 8.31 - lr: 0.000037 - momentum: 0.000000
306
+ 2024-06-23 23:46:53,021 epoch 14 - iter 15/39 - loss 0.00000044 - time (sec): 28.16 - samples/sec: 8.52 - lr: 0.000037 - momentum: 0.000000
307
+ 2024-06-23 23:46:59,960 epoch 14 - iter 18/39 - loss 0.00000042 - time (sec): 35.10 - samples/sec: 8.21 - lr: 0.000037 - momentum: 0.000000
308
+ 2024-06-23 23:47:05,220 epoch 14 - iter 21/39 - loss 0.00000037 - time (sec): 40.36 - samples/sec: 8.33 - lr: 0.000037 - momentum: 0.000000
309
+ 2024-06-23 23:47:10,121 epoch 14 - iter 24/39 - loss 0.00000034 - time (sec): 45.26 - samples/sec: 8.48 - lr: 0.000037 - momentum: 0.000000
310
+ 2024-06-23 23:47:14,955 epoch 14 - iter 27/39 - loss 0.00000035 - time (sec): 50.09 - samples/sec: 8.62 - lr: 0.000037 - momentum: 0.000000
311
+ 2024-06-23 23:47:20,034 epoch 14 - iter 30/39 - loss 0.00550655 - time (sec): 55.17 - samples/sec: 8.70 - lr: 0.000037 - momentum: 0.000000
312
+ 2024-06-23 23:47:27,595 epoch 14 - iter 33/39 - loss 0.00500599 - time (sec): 62.73 - samples/sec: 8.42 - lr: 0.000037 - momentum: 0.000000
313
+ 2024-06-23 23:47:33,013 epoch 14 - iter 36/39 - loss 0.00458946 - time (sec): 68.15 - samples/sec: 8.45 - lr: 0.000036 - momentum: 0.000000
314
+ 2024-06-23 23:47:37,132 epoch 14 - iter 39/39 - loss 0.00438734 - time (sec): 72.27 - samples/sec: 8.54 - lr: 0.000036 - momentum: 0.000000
315
+ 2024-06-23 23:47:37,132 ----------------------------------------------------------------------------------------------------
316
+ 2024-06-23 23:47:37,132 EPOCH 14 done: loss 0.0044 - lr: 0.000036
317
+ 2024-06-23 23:47:41,916 DEV : loss 1.564867377281189 - f1-score (micro avg) 0.8553
318
+ 2024-06-23 23:47:43,632 ----------------------------------------------------------------------------------------------------
319
+ 2024-06-23 23:47:51,205 epoch 15 - iter 3/39 - loss 0.00000192 - time (sec): 7.57 - samples/sec: 6.34 - lr: 0.000036 - momentum: 0.000000
320
+ 2024-06-23 23:47:56,226 epoch 15 - iter 6/39 - loss 0.00000160 - time (sec): 12.59 - samples/sec: 7.62 - lr: 0.000036 - momentum: 0.000000
321
+ 2024-06-23 23:48:03,590 epoch 15 - iter 9/39 - loss 0.00000119 - time (sec): 19.96 - samples/sec: 7.22 - lr: 0.000036 - momentum: 0.000000
322
+ 2024-06-23 23:48:09,817 epoch 15 - iter 12/39 - loss 0.00000146 - time (sec): 26.18 - samples/sec: 7.33 - lr: 0.000036 - momentum: 0.000000
323
+ 2024-06-23 23:48:14,630 epoch 15 - iter 15/39 - loss 0.00000159 - time (sec): 31.00 - samples/sec: 7.74 - lr: 0.000036 - momentum: 0.000000
324
+ 2024-06-23 23:48:20,535 epoch 15 - iter 18/39 - loss 0.00003042 - time (sec): 36.90 - samples/sec: 7.80 - lr: 0.000036 - momentum: 0.000000
325
+ 2024-06-23 23:48:25,523 epoch 15 - iter 21/39 - loss 0.00002633 - time (sec): 41.89 - samples/sec: 8.02 - lr: 0.000036 - momentum: 0.000000
326
+ 2024-06-23 23:48:30,109 epoch 15 - iter 24/39 - loss 0.00002378 - time (sec): 46.48 - samples/sec: 8.26 - lr: 0.000036 - momentum: 0.000000
327
+ 2024-06-23 23:48:36,807 epoch 15 - iter 27/39 - loss 0.00002128 - time (sec): 53.17 - samples/sec: 8.12 - lr: 0.000035 - momentum: 0.000000
328
+ 2024-06-23 23:48:41,596 epoch 15 - iter 30/39 - loss 0.00005866 - time (sec): 57.96 - samples/sec: 8.28 - lr: 0.000035 - momentum: 0.000000
329
+ 2024-06-23 23:48:46,838 epoch 15 - iter 33/39 - loss 0.00005338 - time (sec): 63.21 - samples/sec: 8.35 - lr: 0.000035 - momentum: 0.000000
330
+ 2024-06-23 23:48:51,729 epoch 15 - iter 36/39 - loss 0.00022543 - time (sec): 68.10 - samples/sec: 8.46 - lr: 0.000035 - momentum: 0.000000
331
+ 2024-06-23 23:48:55,746 epoch 15 - iter 39/39 - loss 0.00021046 - time (sec): 72.11 - samples/sec: 8.56 - lr: 0.000035 - momentum: 0.000000
332
+ 2024-06-23 23:48:55,747 ----------------------------------------------------------------------------------------------------
333
+ 2024-06-23 23:48:55,747 EPOCH 15 done: loss 0.0002 - lr: 0.000035
334
+ 2024-06-23 23:49:00,550 DEV : loss 1.6431025266647339 - f1-score (micro avg) 0.8947
335
+ 2024-06-23 23:49:02,263 ----------------------------------------------------------------------------------------------------
336
+ 2024-06-23 23:49:07,994 epoch 16 - iter 3/39 - loss 0.00000012 - time (sec): 5.73 - samples/sec: 8.38 - lr: 0.000035 - momentum: 0.000000
337
+ 2024-06-23 23:49:12,702 epoch 16 - iter 6/39 - loss 0.00001361 - time (sec): 10.44 - samples/sec: 9.20 - lr: 0.000035 - momentum: 0.000000
338
+ 2024-06-23 23:49:17,834 epoch 16 - iter 9/39 - loss 0.00000911 - time (sec): 15.57 - samples/sec: 9.25 - lr: 0.000035 - momentum: 0.000000
339
+ 2024-06-23 23:49:22,603 epoch 16 - iter 12/39 - loss 0.00000783 - time (sec): 20.34 - samples/sec: 9.44 - lr: 0.000035 - momentum: 0.000000
340
+ 2024-06-23 23:49:28,901 epoch 16 - iter 15/39 - loss 0.00000630 - time (sec): 26.64 - samples/sec: 9.01 - lr: 0.000034 - momentum: 0.000000
341
+ 2024-06-23 23:49:33,590 epoch 16 - iter 18/39 - loss 0.00000537 - time (sec): 31.33 - samples/sec: 9.19 - lr: 0.000034 - momentum: 0.000000
342
+ 2024-06-23 23:49:41,448 epoch 16 - iter 21/39 - loss 0.00000466 - time (sec): 39.18 - samples/sec: 8.57 - lr: 0.000034 - momentum: 0.000000
343
+ 2024-06-23 23:49:46,193 epoch 16 - iter 24/39 - loss 0.00000410 - time (sec): 43.93 - samples/sec: 8.74 - lr: 0.000034 - momentum: 0.000000
344
+ 2024-06-23 23:49:51,556 epoch 16 - iter 27/39 - loss 0.00000387 - time (sec): 49.29 - samples/sec: 8.76 - lr: 0.000034 - momentum: 0.000000
345
+ 2024-06-23 23:49:57,993 epoch 16 - iter 30/39 - loss 0.00000350 - time (sec): 55.73 - samples/sec: 8.61 - lr: 0.000034 - momentum: 0.000000
346
+ 2024-06-23 23:50:03,689 epoch 16 - iter 33/39 - loss 0.00000323 - time (sec): 61.42 - samples/sec: 8.60 - lr: 0.000034 - momentum: 0.000000
347
+ 2024-06-23 23:50:08,966 epoch 16 - iter 36/39 - loss 0.00000297 - time (sec): 66.70 - samples/sec: 8.64 - lr: 0.000034 - momentum: 0.000000
348
+ 2024-06-23 23:50:14,750 epoch 16 - iter 39/39 - loss 0.00000279 - time (sec): 72.49 - samples/sec: 8.51 - lr: 0.000034 - momentum: 0.000000
349
+ 2024-06-23 23:50:14,751 ----------------------------------------------------------------------------------------------------
350
+ 2024-06-23 23:50:14,751 EPOCH 16 done: loss 0.0000 - lr: 0.000034
351
+ 2024-06-23 23:50:19,622 DEV : loss 1.6324049234390259 - f1-score (micro avg) 0.8684
352
+ 2024-06-23 23:50:21,218 ----------------------------------------------------------------------------------------------------
353
+ 2024-06-23 23:50:26,329 epoch 17 - iter 3/39 - loss 0.00000024 - time (sec): 5.11 - samples/sec: 9.39 - lr: 0.000034 - momentum: 0.000000
354
+ 2024-06-23 23:50:32,142 epoch 17 - iter 6/39 - loss 0.00000164 - time (sec): 10.92 - samples/sec: 8.79 - lr: 0.000033 - momentum: 0.000000
355
+ 2024-06-23 23:50:38,584 epoch 17 - iter 9/39 - loss 0.00000124 - time (sec): 17.37 - samples/sec: 8.29 - lr: 0.000033 - momentum: 0.000000
356
+ 2024-06-23 23:50:45,354 epoch 17 - iter 12/39 - loss 0.00000096 - time (sec): 24.13 - samples/sec: 7.96 - lr: 0.000033 - momentum: 0.000000
357
+ 2024-06-23 23:50:50,553 epoch 17 - iter 15/39 - loss 0.00000122 - time (sec): 29.33 - samples/sec: 8.18 - lr: 0.000033 - momentum: 0.000000
358
+ 2024-06-23 23:50:55,313 epoch 17 - iter 18/39 - loss 0.00000168 - time (sec): 34.09 - samples/sec: 8.45 - lr: 0.000033 - momentum: 0.000000
359
+ 2024-06-23 23:51:01,865 epoch 17 - iter 21/39 - loss 0.00000145 - time (sec): 40.65 - samples/sec: 8.27 - lr: 0.000033 - momentum: 0.000000
360
+ 2024-06-23 23:51:07,839 epoch 17 - iter 24/39 - loss 0.00000311 - time (sec): 46.62 - samples/sec: 8.24 - lr: 0.000033 - momentum: 0.000000
361
+ 2024-06-23 23:51:14,693 epoch 17 - iter 27/39 - loss 0.00000279 - time (sec): 53.47 - samples/sec: 8.08 - lr: 0.000033 - momentum: 0.000000
362
+ 2024-06-23 23:51:19,818 epoch 17 - iter 30/39 - loss 0.00000253 - time (sec): 58.60 - samples/sec: 8.19 - lr: 0.000033 - momentum: 0.000000
363
+ 2024-06-23 23:51:24,481 epoch 17 - iter 33/39 - loss 0.00000231 - time (sec): 63.26 - samples/sec: 8.35 - lr: 0.000032 - momentum: 0.000000
364
+ 2024-06-23 23:51:29,815 epoch 17 - iter 36/39 - loss 0.00000212 - time (sec): 68.60 - samples/sec: 8.40 - lr: 0.000032 - momentum: 0.000000
365
+ 2024-06-23 23:51:33,764 epoch 17 - iter 39/39 - loss 0.00000200 - time (sec): 72.55 - samples/sec: 8.50 - lr: 0.000032 - momentum: 0.000000
366
+ 2024-06-23 23:51:33,765 ----------------------------------------------------------------------------------------------------
367
+ 2024-06-23 23:51:33,765 EPOCH 17 done: loss 0.0000 - lr: 0.000032
368
+ 2024-06-23 23:51:38,698 DEV : loss 1.6667038202285767 - f1-score (micro avg) 0.8947
369
+ 2024-06-23 23:51:40,298 ----------------------------------------------------------------------------------------------------
370
+ 2024-06-23 23:51:46,093 epoch 18 - iter 3/39 - loss 0.00000386 - time (sec): 5.79 - samples/sec: 8.29 - lr: 0.000032 - momentum: 0.000000
371
+ 2024-06-23 23:51:52,974 epoch 18 - iter 6/39 - loss 0.00000209 - time (sec): 12.67 - samples/sec: 7.57 - lr: 0.000032 - momentum: 0.000000
372
+ 2024-06-23 23:51:57,585 epoch 18 - iter 9/39 - loss 0.00000145 - time (sec): 17.29 - samples/sec: 8.33 - lr: 0.000032 - momentum: 0.000000
373
+ 2024-06-23 23:52:02,370 epoch 18 - iter 12/39 - loss 0.00000112 - time (sec): 22.07 - samples/sec: 8.70 - lr: 0.000032 - momentum: 0.000000
374
+ 2024-06-23 23:52:07,154 epoch 18 - iter 15/39 - loss 0.00000090 - time (sec): 26.85 - samples/sec: 8.94 - lr: 0.000032 - momentum: 0.000000
375
+ 2024-06-23 23:52:14,195 epoch 18 - iter 18/39 - loss 0.00000079 - time (sec): 33.90 - samples/sec: 8.50 - lr: 0.000032 - momentum: 0.000000
376
+ 2024-06-23 23:52:20,573 epoch 18 - iter 21/39 - loss 0.00000069 - time (sec): 40.27 - samples/sec: 8.34 - lr: 0.000032 - momentum: 0.000000
377
+ 2024-06-23 23:52:26,312 epoch 18 - iter 24/39 - loss 0.00000062 - time (sec): 46.01 - samples/sec: 8.35 - lr: 0.000031 - momentum: 0.000000
378
+ 2024-06-23 23:52:31,041 epoch 18 - iter 27/39 - loss 0.00000062 - time (sec): 50.74 - samples/sec: 8.51 - lr: 0.000031 - momentum: 0.000000
379
+ 2024-06-23 23:52:36,077 epoch 18 - iter 30/39 - loss 0.00000057 - time (sec): 55.78 - samples/sec: 8.61 - lr: 0.000031 - momentum: 0.000000
380
+ 2024-06-23 23:52:42,035 epoch 18 - iter 33/39 - loss 0.00000069 - time (sec): 61.73 - samples/sec: 8.55 - lr: 0.000031 - momentum: 0.000000
381
+ 2024-06-23 23:52:47,259 epoch 18 - iter 36/39 - loss 0.00000076 - time (sec): 66.96 - samples/sec: 8.60 - lr: 0.000031 - momentum: 0.000000
382
+ 2024-06-23 23:52:52,788 epoch 18 - iter 39/39 - loss 0.00000071 - time (sec): 72.49 - samples/sec: 8.51 - lr: 0.000031 - momentum: 0.000000
383
+ 2024-06-23 23:52:52,788 ----------------------------------------------------------------------------------------------------
384
+ 2024-06-23 23:52:52,788 EPOCH 18 done: loss 0.0000 - lr: 0.000031
385
+ 2024-06-23 23:52:57,710 DEV : loss 1.6734051704406738 - f1-score (micro avg) 0.8947
386
+ 2024-06-23 23:52:59,305 ----------------------------------------------------------------------------------------------------
387
+ 2024-06-23 23:53:04,600 epoch 19 - iter 3/39 - loss 0.00000006 - time (sec): 5.29 - samples/sec: 9.07 - lr: 0.000031 - momentum: 0.000000
388
+ 2024-06-23 23:53:09,523 epoch 19 - iter 6/39 - loss 0.00000009 - time (sec): 10.22 - samples/sec: 9.40 - lr: 0.000031 - momentum: 0.000000
389
+ 2024-06-23 23:53:14,402 epoch 19 - iter 9/39 - loss 0.00000056 - time (sec): 15.10 - samples/sec: 9.54 - lr: 0.000031 - momentum: 0.000000
390
+ 2024-06-23 23:53:19,255 epoch 19 - iter 12/39 - loss 0.00000043 - time (sec): 19.95 - samples/sec: 9.62 - lr: 0.000030 - momentum: 0.000000
391
+ 2024-06-23 23:53:24,050 epoch 19 - iter 15/39 - loss 0.00000035 - time (sec): 24.74 - samples/sec: 9.70 - lr: 0.000030 - momentum: 0.000000
392
+ 2024-06-23 23:53:28,857 epoch 19 - iter 18/39 - loss 0.00000030 - time (sec): 29.55 - samples/sec: 9.75 - lr: 0.000030 - momentum: 0.000000
393
+ 2024-06-23 23:53:35,437 epoch 19 - iter 21/39 - loss 0.00000079 - time (sec): 36.13 - samples/sec: 9.30 - lr: 0.000030 - momentum: 0.000000
394
+ 2024-06-23 23:53:41,864 epoch 19 - iter 24/39 - loss 0.00000073 - time (sec): 42.56 - samples/sec: 9.02 - lr: 0.000030 - momentum: 0.000000
395
+ 2024-06-23 23:53:46,592 epoch 19 - iter 27/39 - loss 0.00000066 - time (sec): 47.29 - samples/sec: 9.14 - lr: 0.000030 - momentum: 0.000000
396
+ 2024-06-23 23:53:52,506 epoch 19 - iter 30/39 - loss 0.00000065 - time (sec): 53.20 - samples/sec: 9.02 - lr: 0.000030 - momentum: 0.000000
397
+ 2024-06-23 23:53:58,434 epoch 19 - iter 33/39 - loss 0.00000060 - time (sec): 59.13 - samples/sec: 8.93 - lr: 0.000030 - momentum: 0.000000
398
+ 2024-06-23 23:54:06,388 epoch 19 - iter 36/39 - loss 0.00000057 - time (sec): 67.08 - samples/sec: 8.59 - lr: 0.000030 - momentum: 0.000000
399
+ 2024-06-23 23:54:11,710 epoch 19 - iter 39/39 - loss 0.00000053 - time (sec): 72.40 - samples/sec: 8.52 - lr: 0.000030 - momentum: 0.000000
400
+ 2024-06-23 23:54:11,711 ----------------------------------------------------------------------------------------------------
401
+ 2024-06-23 23:54:11,711 EPOCH 19 done: loss 0.0000 - lr: 0.000030
402
+ 2024-06-23 23:54:16,561 DEV : loss 1.6832987070083618 - f1-score (micro avg) 0.8947
403
+ 2024-06-23 23:54:18,283 ----------------------------------------------------------------------------------------------------
404
+ 2024-06-23 23:54:23,245 epoch 20 - iter 3/39 - loss 0.00000062 - time (sec): 4.96 - samples/sec: 9.68 - lr: 0.000029 - momentum: 0.000000
405
+ 2024-06-23 23:54:29,074 epoch 20 - iter 6/39 - loss 0.00000034 - time (sec): 10.79 - samples/sec: 8.90 - lr: 0.000029 - momentum: 0.000000
406
+ 2024-06-23 23:54:34,112 epoch 20 - iter 9/39 - loss 0.00000028 - time (sec): 15.83 - samples/sec: 9.10 - lr: 0.000029 - momentum: 0.000000
407
+ 2024-06-23 23:54:38,954 epoch 20 - iter 12/39 - loss 0.00000027 - time (sec): 20.67 - samples/sec: 9.29 - lr: 0.000029 - momentum: 0.000000
408
+ 2024-06-23 23:54:43,982 epoch 20 - iter 15/39 - loss 0.00000064 - time (sec): 25.70 - samples/sec: 9.34 - lr: 0.000029 - momentum: 0.000000
409
+ 2024-06-23 23:54:48,652 epoch 20 - iter 18/39 - loss 0.00000062 - time (sec): 30.37 - samples/sec: 9.48 - lr: 0.000029 - momentum: 0.000000
410
+ 2024-06-23 23:54:54,811 epoch 20 - iter 21/39 - loss 0.00000055 - time (sec): 36.53 - samples/sec: 9.20 - lr: 0.000029 - momentum: 0.000000
411
+ 2024-06-23 23:55:00,691 epoch 20 - iter 24/39 - loss 0.00000048 - time (sec): 42.41 - samples/sec: 9.06 - lr: 0.000029 - momentum: 0.000000
412
+ 2024-06-23 23:55:07,972 epoch 20 - iter 27/39 - loss 0.00000043 - time (sec): 49.69 - samples/sec: 8.69 - lr: 0.000029 - momentum: 0.000000
413
+ 2024-06-23 23:55:14,702 epoch 20 - iter 30/39 - loss 0.00000041 - time (sec): 56.42 - samples/sec: 8.51 - lr: 0.000028 - momentum: 0.000000
414
+ 2024-06-23 23:55:19,760 epoch 20 - iter 33/39 - loss 0.00000038 - time (sec): 61.48 - samples/sec: 8.59 - lr: 0.000028 - momentum: 0.000000
415
+ 2024-06-23 23:55:26,384 epoch 20 - iter 36/39 - loss 0.00000038 - time (sec): 68.10 - samples/sec: 8.46 - lr: 0.000028 - momentum: 0.000000
416
+ 2024-06-23 23:55:30,414 epoch 20 - iter 39/39 - loss 0.00000036 - time (sec): 72.13 - samples/sec: 8.55 - lr: 0.000028 - momentum: 0.000000
417
+ 2024-06-23 23:55:30,414 ----------------------------------------------------------------------------------------------------
418
+ 2024-06-23 23:55:30,415 EPOCH 20 done: loss 0.0000 - lr: 0.000028
419
+ 2024-06-23 23:55:35,248 DEV : loss 1.6803444623947144 - f1-score (micro avg) 0.8947
420
+ 2024-06-23 23:55:36,942 ----------------------------------------------------------------------------------------------------
421
+ 2024-06-23 23:55:43,422 epoch 21 - iter 3/39 - loss 0.00000011 - time (sec): 6.48 - samples/sec: 7.41 - lr: 0.000028 - momentum: 0.000000
422
+ 2024-06-23 23:55:48,506 epoch 21 - iter 6/39 - loss 0.00000009 - time (sec): 11.56 - samples/sec: 8.30 - lr: 0.000028 - momentum: 0.000000
423
+ 2024-06-23 23:55:53,273 epoch 21 - iter 9/39 - loss 0.00000009 - time (sec): 16.33 - samples/sec: 8.82 - lr: 0.000028 - momentum: 0.000000
424
+ 2024-06-23 23:55:59,004 epoch 21 - iter 12/39 - loss 0.00000009 - time (sec): 22.06 - samples/sec: 8.70 - lr: 0.000028 - momentum: 0.000000
425
+ 2024-06-23 23:56:03,991 epoch 21 - iter 15/39 - loss 0.00000104 - time (sec): 27.05 - samples/sec: 8.87 - lr: 0.000028 - momentum: 0.000000
426
+ 2024-06-23 23:56:10,166 epoch 21 - iter 18/39 - loss 0.00000090 - time (sec): 33.22 - samples/sec: 8.67 - lr: 0.000028 - momentum: 0.000000
427
+ 2024-06-23 23:56:14,886 epoch 21 - iter 21/39 - loss 0.00000079 - time (sec): 37.94 - samples/sec: 8.86 - lr: 0.000027 - momentum: 0.000000
428
+ 2024-06-23 23:56:20,191 epoch 21 - iter 24/39 - loss 0.00000069 - time (sec): 43.25 - samples/sec: 8.88 - lr: 0.000027 - momentum: 0.000000
429
+ 2024-06-23 23:56:26,244 epoch 21 - iter 27/39 - loss 0.00000068 - time (sec): 49.30 - samples/sec: 8.76 - lr: 0.000027 - momentum: 0.000000
430
+ 2024-06-23 23:56:31,439 epoch 21 - iter 30/39 - loss 0.00000062 - time (sec): 54.50 - samples/sec: 8.81 - lr: 0.000027 - momentum: 0.000000
431
+ 2024-06-23 23:56:38,526 epoch 21 - iter 33/39 - loss 0.00000070 - time (sec): 61.58 - samples/sec: 8.57 - lr: 0.000027 - momentum: 0.000000
432
+ 2024-06-23 23:56:43,558 epoch 21 - iter 36/39 - loss 0.00000065 - time (sec): 66.62 - samples/sec: 8.65 - lr: 0.000027 - momentum: 0.000000
433
+ 2024-06-23 23:56:49,100 epoch 21 - iter 39/39 - loss 0.00000061 - time (sec): 72.16 - samples/sec: 8.55 - lr: 0.000027 - momentum: 0.000000
434
+ 2024-06-23 23:56:49,100 ----------------------------------------------------------------------------------------------------
435
+ 2024-06-23 23:56:49,100 EPOCH 21 done: loss 0.0000 - lr: 0.000027
436
+ 2024-06-23 23:56:53,869 DEV : loss 1.6836782693862915 - f1-score (micro avg) 0.8947
437
+ 2024-06-23 23:56:55,587 ----------------------------------------------------------------------------------------------------
438
+ 2024-06-23 23:57:00,339 epoch 22 - iter 3/39 - loss 0.00000070 - time (sec): 4.75 - samples/sec: 10.10 - lr: 0.000027 - momentum: 0.000000
439
+ 2024-06-23 23:57:05,168 epoch 22 - iter 6/39 - loss 0.00000040 - time (sec): 9.58 - samples/sec: 10.02 - lr: 0.000027 - momentum: 0.000000
440
+ 2024-06-23 23:57:09,879 epoch 22 - iter 9/39 - loss 0.00000028 - time (sec): 14.29 - samples/sec: 10.08 - lr: 0.000026 - momentum: 0.000000
441
+ 2024-06-23 23:57:15,130 epoch 22 - iter 12/39 - loss 0.00000022 - time (sec): 19.54 - samples/sec: 9.82 - lr: 0.000026 - momentum: 0.000000
442
+ 2024-06-23 23:57:20,147 epoch 22 - iter 15/39 - loss 0.00000019 - time (sec): 24.56 - samples/sec: 9.77 - lr: 0.000026 - momentum: 0.000000
443
+ 2024-06-23 23:57:28,906 epoch 22 - iter 18/39 - loss 0.00000045 - time (sec): 33.32 - samples/sec: 8.64 - lr: 0.000026 - momentum: 0.000000
444
+ 2024-06-23 23:57:33,703 epoch 22 - iter 21/39 - loss 0.00000040 - time (sec): 38.11 - samples/sec: 8.82 - lr: 0.000026 - momentum: 0.000000
445
+ 2024-06-23 23:57:38,431 epoch 22 - iter 24/39 - loss 0.00000037 - time (sec): 42.84 - samples/sec: 8.96 - lr: 0.000026 - momentum: 0.000000
446
+ 2024-06-23 23:57:44,678 epoch 22 - iter 27/39 - loss 0.00000039 - time (sec): 49.09 - samples/sec: 8.80 - lr: 0.000026 - momentum: 0.000000
447
+ 2024-06-23 23:57:49,384 epoch 22 - iter 30/39 - loss 0.00000037 - time (sec): 53.80 - samples/sec: 8.92 - lr: 0.000026 - momentum: 0.000000
448
+ 2024-06-23 23:57:55,518 epoch 22 - iter 33/39 - loss 0.00000036 - time (sec): 59.93 - samples/sec: 8.81 - lr: 0.000026 - momentum: 0.000000
449
+ 2024-06-23 23:58:01,846 epoch 22 - iter 36/39 - loss 0.00000034 - time (sec): 66.26 - samples/sec: 8.69 - lr: 0.000026 - momentum: 0.000000
450
+ 2024-06-23 23:58:07,646 epoch 22 - iter 39/39 - loss 0.00000032 - time (sec): 72.06 - samples/sec: 8.56 - lr: 0.000025 - momentum: 0.000000
451
+ 2024-06-23 23:58:07,647 ----------------------------------------------------------------------------------------------------
452
+ 2024-06-23 23:58:07,647 EPOCH 22 done: loss 0.0000 - lr: 0.000025
453
+ 2024-06-23 23:58:12,485 DEV : loss 1.6798239946365356 - f1-score (micro avg) 0.8947
454
+ 2024-06-23 23:58:14,187 ----------------------------------------------------------------------------------------------------
455
+ 2024-06-23 23:58:19,952 epoch 23 - iter 3/39 - loss 0.00000012 - time (sec): 5.76 - samples/sec: 8.33 - lr: 0.000025 - momentum: 0.000000
456
+ 2024-06-23 23:58:24,724 epoch 23 - iter 6/39 - loss 0.00000025 - time (sec): 10.54 - samples/sec: 9.11 - lr: 0.000025 - momentum: 0.000000
457
+ 2024-06-23 23:58:29,553 epoch 23 - iter 9/39 - loss 0.00000020 - time (sec): 15.36 - samples/sec: 9.37 - lr: 0.000025 - momentum: 0.000000
458
+ 2024-06-23 23:58:34,240 epoch 23 - iter 12/39 - loss 0.00000017 - time (sec): 20.05 - samples/sec: 9.58 - lr: 0.000025 - momentum: 0.000000
459
+ 2024-06-23 23:58:39,532 epoch 23 - iter 15/39 - loss 0.00000016 - time (sec): 25.34 - samples/sec: 9.47 - lr: 0.000025 - momentum: 0.000000
460
+ 2024-06-23 23:58:46,114 epoch 23 - iter 18/39 - loss 0.00000016 - time (sec): 31.93 - samples/sec: 9.02 - lr: 0.000025 - momentum: 0.000000
461
+ 2024-06-23 23:58:51,076 epoch 23 - iter 21/39 - loss 0.00000017 - time (sec): 36.89 - samples/sec: 9.11 - lr: 0.000025 - momentum: 0.000000
462
+ 2024-06-23 23:58:58,437 epoch 23 - iter 24/39 - loss 0.00000016 - time (sec): 44.25 - samples/sec: 8.68 - lr: 0.000025 - momentum: 0.000000
463
+ 2024-06-23 23:59:05,351 epoch 23 - iter 27/39 - loss 0.00000016 - time (sec): 51.16 - samples/sec: 8.44 - lr: 0.000024 - momentum: 0.000000
464
+ 2024-06-23 23:59:11,049 epoch 23 - iter 30/39 - loss 0.00000015 - time (sec): 56.86 - samples/sec: 8.44 - lr: 0.000024 - momentum: 0.000000
465
+ 2024-06-23 23:59:16,119 epoch 23 - iter 33/39 - loss 0.00000066 - time (sec): 61.93 - samples/sec: 8.53 - lr: 0.000024 - momentum: 0.000000
466
+ 2024-06-23 23:59:21,829 epoch 23 - iter 36/39 - loss 0.00000064 - time (sec): 67.64 - samples/sec: 8.52 - lr: 0.000024 - momentum: 0.000000
467
+ 2024-06-23 23:59:25,878 epoch 23 - iter 39/39 - loss 0.00000060 - time (sec): 71.69 - samples/sec: 8.61 - lr: 0.000024 - momentum: 0.000000
468
+ 2024-06-23 23:59:25,878 ----------------------------------------------------------------------------------------------------
469
+ 2024-06-23 23:59:25,878 EPOCH 23 done: loss 0.0000 - lr: 0.000024
470
+ 2024-06-23 23:59:30,684 DEV : loss 1.686423897743225 - f1-score (micro avg) 0.8947
471
+ 2024-06-23 23:59:32,382 ----------------------------------------------------------------------------------------------------
472
+ 2024-06-23 23:59:37,585 epoch 24 - iter 3/39 - loss 0.00000041 - time (sec): 5.20 - samples/sec: 9.23 - lr: 0.000024 - momentum: 0.000000
473
+ 2024-06-23 23:59:42,342 epoch 24 - iter 6/39 - loss 0.00000028 - time (sec): 9.96 - samples/sec: 9.64 - lr: 0.000024 - momentum: 0.000000
474
+ 2024-06-23 23:59:48,252 epoch 24 - iter 9/39 - loss 0.00000020 - time (sec): 15.87 - samples/sec: 9.07 - lr: 0.000024 - momentum: 0.000000
475
+ 2024-06-23 23:59:53,044 epoch 24 - iter 12/39 - loss 0.00000017 - time (sec): 20.66 - samples/sec: 9.29 - lr: 0.000024 - momentum: 0.000000
476
+ 2024-06-23 23:59:58,797 epoch 24 - iter 15/39 - loss 0.00000020 - time (sec): 26.41 - samples/sec: 9.09 - lr: 0.000024 - momentum: 0.000000
477
+ 2024-06-24 00:00:03,629 epoch 24 - iter 18/39 - loss 0.00000017 - time (sec): 31.25 - samples/sec: 9.22 - lr: 0.000023 - momentum: 0.000000
478
+ 2024-06-24 00:00:08,808 epoch 24 - iter 21/39 - loss 0.00000015 - time (sec): 36.42 - samples/sec: 9.22 - lr: 0.000023 - momentum: 0.000000
479
+ 2024-06-24 00:00:14,820 epoch 24 - iter 24/39 - loss 0.00000014 - time (sec): 42.44 - samples/sec: 9.05 - lr: 0.000023 - momentum: 0.000000
480
+ 2024-06-24 00:00:20,596 epoch 24 - iter 27/39 - loss 0.00000019 - time (sec): 48.21 - samples/sec: 8.96 - lr: 0.000023 - momentum: 0.000000
481
+ 2024-06-24 00:00:26,162 epoch 24 - iter 30/39 - loss 0.00000018 - time (sec): 53.78 - samples/sec: 8.93 - lr: 0.000023 - momentum: 0.000000
482
+ 2024-06-24 00:00:30,796 epoch 24 - iter 33/39 - loss 0.00000020 - time (sec): 58.41 - samples/sec: 9.04 - lr: 0.000023 - momentum: 0.000000
483
+ 2024-06-24 00:00:40,090 epoch 24 - iter 36/39 - loss 0.00000019 - time (sec): 67.71 - samples/sec: 8.51 - lr: 0.000023 - momentum: 0.000000
484
+ 2024-06-24 00:00:44,496 epoch 24 - iter 39/39 - loss 0.00000018 - time (sec): 72.11 - samples/sec: 8.56 - lr: 0.000023 - momentum: 0.000000
485
+ 2024-06-24 00:00:44,497 ----------------------------------------------------------------------------------------------------
486
+ 2024-06-24 00:00:44,497 EPOCH 24 done: loss 0.0000 - lr: 0.000023
487
+ 2024-06-24 00:00:49,348 DEV : loss 1.6934013366699219 - f1-score (micro avg) 0.8947
488
+ 2024-06-24 00:00:51,073 ----------------------------------------------------------------------------------------------------
489
+ 2024-06-24 00:00:55,786 epoch 25 - iter 3/39 - loss 0.00000015 - time (sec): 4.71 - samples/sec: 10.19 - lr: 0.000023 - momentum: 0.000000
490
+ 2024-06-24 00:01:01,366 epoch 25 - iter 6/39 - loss 0.00000032 - time (sec): 10.29 - samples/sec: 9.33 - lr: 0.000022 - momentum: 0.000000
491
+ 2024-06-24 00:01:06,852 epoch 25 - iter 9/39 - loss 0.00000051 - time (sec): 15.78 - samples/sec: 9.13 - lr: 0.000022 - momentum: 0.000000
492
+ 2024-06-24 00:01:11,651 epoch 25 - iter 12/39 - loss 0.00000039 - time (sec): 20.58 - samples/sec: 9.33 - lr: 0.000022 - momentum: 0.000000
493
+ 2024-06-24 00:01:16,386 epoch 25 - iter 15/39 - loss 0.00000037 - time (sec): 25.31 - samples/sec: 9.48 - lr: 0.000022 - momentum: 0.000000
494
+ 2024-06-24 00:01:21,284 epoch 25 - iter 18/39 - loss 0.00000033 - time (sec): 30.21 - samples/sec: 9.53 - lr: 0.000022 - momentum: 0.000000
495
+ 2024-06-24 00:01:25,999 epoch 25 - iter 21/39 - loss 0.00000030 - time (sec): 34.93 - samples/sec: 9.62 - lr: 0.000022 - momentum: 0.000000
496
+ 2024-06-24 00:01:31,195 epoch 25 - iter 24/39 - loss 0.00000026 - time (sec): 40.12 - samples/sec: 9.57 - lr: 0.000022 - momentum: 0.000000
497
+ 2024-06-24 00:01:38,182 epoch 25 - iter 27/39 - loss 0.00000025 - time (sec): 47.11 - samples/sec: 9.17 - lr: 0.000022 - momentum: 0.000000
498
+ 2024-06-24 00:01:44,519 epoch 25 - iter 30/39 - loss 0.00000026 - time (sec): 53.45 - samples/sec: 8.98 - lr: 0.000022 - momentum: 0.000000
499
+ 2024-06-24 00:01:51,469 epoch 25 - iter 33/39 - loss 0.00000024 - time (sec): 60.39 - samples/sec: 8.74 - lr: 0.000022 - momentum: 0.000000
500
+ 2024-06-24 00:01:58,551 epoch 25 - iter 36/39 - loss 0.00000023 - time (sec): 67.48 - samples/sec: 8.54 - lr: 0.000021 - momentum: 0.000000
501
+ 2024-06-24 00:02:03,222 epoch 25 - iter 39/39 - loss 0.00000029 - time (sec): 72.15 - samples/sec: 8.55 - lr: 0.000021 - momentum: 0.000000
502
+ 2024-06-24 00:02:03,222 ----------------------------------------------------------------------------------------------------
503
+ 2024-06-24 00:02:03,222 EPOCH 25 done: loss 0.0000 - lr: 0.000021
504
+ 2024-06-24 00:02:08,000 DEV : loss 1.6937851905822754 - f1-score (micro avg) 0.8947
505
+ 2024-06-24 00:02:09,719 ----------------------------------------------------------------------------------------------------
506
+ 2024-06-24 00:02:15,885 epoch 26 - iter 3/39 - loss 0.00000005 - time (sec): 6.16 - samples/sec: 7.79 - lr: 0.000021 - momentum: 0.000000
507
+ 2024-06-24 00:02:20,586 epoch 26 - iter 6/39 - loss 0.00000007 - time (sec): 10.87 - samples/sec: 8.84 - lr: 0.000021 - momentum: 0.000000
508
+ 2024-06-24 00:02:26,619 epoch 26 - iter 9/39 - loss 0.00000007 - time (sec): 16.90 - samples/sec: 8.52 - lr: 0.000021 - momentum: 0.000000
509
+ 2024-06-24 00:02:33,062 epoch 26 - iter 12/39 - loss 0.00000006 - time (sec): 23.34 - samples/sec: 8.23 - lr: 0.000021 - momentum: 0.000000
510
+ 2024-06-24 00:02:39,697 epoch 26 - iter 15/39 - loss 0.00000005 - time (sec): 29.98 - samples/sec: 8.01 - lr: 0.000021 - momentum: 0.000000
511
+ 2024-06-24 00:02:44,696 epoch 26 - iter 18/39 - loss 0.00000008 - time (sec): 34.98 - samples/sec: 8.23 - lr: 0.000021 - momentum: 0.000000
512
+ 2024-06-24 00:02:49,629 epoch 26 - iter 21/39 - loss 0.00000007 - time (sec): 39.91 - samples/sec: 8.42 - lr: 0.000021 - momentum: 0.000000
513
+ 2024-06-24 00:02:55,530 epoch 26 - iter 24/39 - loss 0.00000012 - time (sec): 45.81 - samples/sec: 8.38 - lr: 0.000020 - momentum: 0.000000
514
+ 2024-06-24 00:03:00,168 epoch 26 - iter 27/39 - loss 0.00000012 - time (sec): 50.45 - samples/sec: 8.56 - lr: 0.000020 - momentum: 0.000000
515
+ 2024-06-24 00:03:05,837 epoch 26 - iter 30/39 - loss 0.00000012 - time (sec): 56.12 - samples/sec: 8.55 - lr: 0.000020 - momentum: 0.000000
516
+ 2024-06-24 00:03:11,122 epoch 26 - iter 33/39 - loss 0.00000011 - time (sec): 61.40 - samples/sec: 8.60 - lr: 0.000020 - momentum: 0.000000
517
+ 2024-06-24 00:03:16,031 epoch 26 - iter 36/39 - loss 0.00000013 - time (sec): 66.31 - samples/sec: 8.69 - lr: 0.000020 - momentum: 0.000000
518
+ 2024-06-24 00:03:21,462 epoch 26 - iter 39/39 - loss 0.00000013 - time (sec): 71.74 - samples/sec: 8.60 - lr: 0.000020 - momentum: 0.000000
519
+ 2024-06-24 00:03:21,462 ----------------------------------------------------------------------------------------------------
520
+ 2024-06-24 00:03:21,462 EPOCH 26 done: loss 0.0000 - lr: 0.000020
521
+ 2024-06-24 00:03:26,369 DEV : loss 1.6954692602157593 - f1-score (micro avg) 0.8947
522
+ 2024-06-24 00:03:27,965 ----------------------------------------------------------------------------------------------------
523
+ 2024-06-24 00:03:32,943 epoch 27 - iter 3/39 - loss 0.00000027 - time (sec): 4.98 - samples/sec: 9.64 - lr: 0.000020 - momentum: 0.000000
524
+ 2024-06-24 00:03:37,755 epoch 27 - iter 6/39 - loss 0.00000040 - time (sec): 9.79 - samples/sec: 9.81 - lr: 0.000020 - momentum: 0.000000
525
+ 2024-06-24 00:03:45,593 epoch 27 - iter 9/39 - loss 0.00000031 - time (sec): 17.63 - samples/sec: 8.17 - lr: 0.000020 - momentum: 0.000000
526
+ 2024-06-24 00:03:50,561 epoch 27 - iter 12/39 - loss 0.00000026 - time (sec): 22.59 - samples/sec: 8.50 - lr: 0.000020 - momentum: 0.000000
527
+ 2024-06-24 00:03:56,047 epoch 27 - iter 15/39 - loss 0.00000021 - time (sec): 28.08 - samples/sec: 8.55 - lr: 0.000019 - momentum: 0.000000
528
+ 2024-06-24 00:04:00,670 epoch 27 - iter 18/39 - loss 0.00000019 - time (sec): 32.70 - samples/sec: 8.81 - lr: 0.000019 - momentum: 0.000000
529
+ 2024-06-24 00:04:05,898 epoch 27 - iter 21/39 - loss 0.00000019 - time (sec): 37.93 - samples/sec: 8.86 - lr: 0.000019 - momentum: 0.000000
530
+ 2024-06-24 00:04:12,467 epoch 27 - iter 24/39 - loss 0.00000017 - time (sec): 44.50 - samples/sec: 8.63 - lr: 0.000019 - momentum: 0.000000
531
+ 2024-06-24 00:04:17,141 epoch 27 - iter 27/39 - loss 0.00000022 - time (sec): 49.17 - samples/sec: 8.79 - lr: 0.000019 - momentum: 0.000000
532
+ 2024-06-24 00:04:23,666 epoch 27 - iter 30/39 - loss 0.00000020 - time (sec): 55.70 - samples/sec: 8.62 - lr: 0.000019 - momentum: 0.000000
533
+ 2024-06-24 00:04:30,842 epoch 27 - iter 33/39 - loss 0.00000019 - time (sec): 62.88 - samples/sec: 8.40 - lr: 0.000019 - momentum: 0.000000
534
+ 2024-06-24 00:04:35,619 epoch 27 - iter 36/39 - loss 0.00000017 - time (sec): 67.65 - samples/sec: 8.51 - lr: 0.000019 - momentum: 0.000000
535
+ 2024-06-24 00:04:40,105 epoch 27 - iter 39/39 - loss 0.00000018 - time (sec): 72.14 - samples/sec: 8.55 - lr: 0.000019 - momentum: 0.000000
536
+ 2024-06-24 00:04:40,106 ----------------------------------------------------------------------------------------------------
537
+ 2024-06-24 00:04:40,106 EPOCH 27 done: loss 0.0000 - lr: 0.000019
538
+ 2024-06-24 00:04:44,881 DEV : loss 1.6968917846679688 - f1-score (micro avg) 0.8947
539
+ 2024-06-24 00:04:46,603 ----------------------------------------------------------------------------------------------------
540
+ 2024-06-24 00:04:51,490 epoch 28 - iter 3/39 - loss 0.00000003 - time (sec): 4.89 - samples/sec: 9.82 - lr: 0.000018 - momentum: 0.000000
541
+ 2024-06-24 00:04:57,535 epoch 28 - iter 6/39 - loss 0.00000011 - time (sec): 10.93 - samples/sec: 8.78 - lr: 0.000018 - momentum: 0.000000
542
+ 2024-06-24 00:05:02,732 epoch 28 - iter 9/39 - loss 0.00000019 - time (sec): 16.13 - samples/sec: 8.93 - lr: 0.000018 - momentum: 0.000000
543
+ 2024-06-24 00:05:09,142 epoch 28 - iter 12/39 - loss 0.00000017 - time (sec): 22.54 - samples/sec: 8.52 - lr: 0.000018 - momentum: 0.000000
544
+ 2024-06-24 00:05:13,949 epoch 28 - iter 15/39 - loss 0.00000014 - time (sec): 27.35 - samples/sec: 8.78 - lr: 0.000018 - momentum: 0.000000
545
+ 2024-06-24 00:05:19,474 epoch 28 - iter 18/39 - loss 0.00000017 - time (sec): 32.87 - samples/sec: 8.76 - lr: 0.000018 - momentum: 0.000000
546
+ 2024-06-24 00:05:26,520 epoch 28 - iter 21/39 - loss 0.00000016 - time (sec): 39.92 - samples/sec: 8.42 - lr: 0.000018 - momentum: 0.000000
547
+ 2024-06-24 00:05:31,232 epoch 28 - iter 24/39 - loss 0.00000014 - time (sec): 44.63 - samples/sec: 8.60 - lr: 0.000018 - momentum: 0.000000
548
+ 2024-06-24 00:05:36,445 epoch 28 - iter 27/39 - loss 0.00000014 - time (sec): 49.84 - samples/sec: 8.67 - lr: 0.000018 - momentum: 0.000000
549
+ 2024-06-24 00:05:42,669 epoch 28 - iter 30/39 - loss 0.00000015 - time (sec): 56.07 - samples/sec: 8.56 - lr: 0.000018 - momentum: 0.000000
550
+ 2024-06-24 00:05:48,598 epoch 28 - iter 33/39 - loss 0.00000016 - time (sec): 61.99 - samples/sec: 8.52 - lr: 0.000017 - momentum: 0.000000
551
+ 2024-06-24 00:05:53,350 epoch 28 - iter 36/39 - loss 0.00000016 - time (sec): 66.75 - samples/sec: 8.63 - lr: 0.000017 - momentum: 0.000000
552
+ 2024-06-24 00:05:58,693 epoch 28 - iter 39/39 - loss 0.00000016 - time (sec): 72.09 - samples/sec: 8.56 - lr: 0.000017 - momentum: 0.000000
553
+ 2024-06-24 00:05:58,694 ----------------------------------------------------------------------------------------------------
554
+ 2024-06-24 00:05:58,694 EPOCH 28 done: loss 0.0000 - lr: 0.000017
555
+ 2024-06-24 00:06:03,494 DEV : loss 1.6977306604385376 - f1-score (micro avg) 0.8947
556
+ 2024-06-24 00:06:05,185 ----------------------------------------------------------------------------------------------------
557
+ 2024-06-24 00:06:10,371 epoch 29 - iter 3/39 - loss 0.00000039 - time (sec): 5.19 - samples/sec: 9.26 - lr: 0.000017 - momentum: 0.000000
558
+ 2024-06-24 00:06:15,181 epoch 29 - iter 6/39 - loss 0.00000024 - time (sec): 10.00 - samples/sec: 9.60 - lr: 0.000017 - momentum: 0.000000
559
+ 2024-06-24 00:06:21,095 epoch 29 - iter 9/39 - loss 0.00000017 - time (sec): 15.91 - samples/sec: 9.05 - lr: 0.000017 - momentum: 0.000000
560
+ 2024-06-24 00:06:26,316 epoch 29 - iter 12/39 - loss 0.00000015 - time (sec): 21.13 - samples/sec: 9.09 - lr: 0.000017 - momentum: 0.000000
561
+ 2024-06-24 00:06:32,910 epoch 29 - iter 15/39 - loss 0.00000013 - time (sec): 27.72 - samples/sec: 8.66 - lr: 0.000017 - momentum: 0.000000
562
+ 2024-06-24 00:06:39,431 epoch 29 - iter 18/39 - loss 0.00000011 - time (sec): 34.25 - samples/sec: 8.41 - lr: 0.000017 - momentum: 0.000000
563
+ 2024-06-24 00:06:44,951 epoch 29 - iter 21/39 - loss 0.00000015 - time (sec): 39.77 - samples/sec: 8.45 - lr: 0.000016 - momentum: 0.000000
564
+ 2024-06-24 00:06:49,789 epoch 29 - iter 24/39 - loss 0.00000058 - time (sec): 44.60 - samples/sec: 8.61 - lr: 0.000016 - momentum: 0.000000
565
+ 2024-06-24 00:06:54,794 epoch 29 - iter 27/39 - loss 0.00000052 - time (sec): 49.61 - samples/sec: 8.71 - lr: 0.000016 - momentum: 0.000000
566
+ 2024-06-24 00:07:00,697 epoch 29 - iter 30/39 - loss 0.00000056 - time (sec): 55.51 - samples/sec: 8.65 - lr: 0.000016 - momentum: 0.000000
567
+ 2024-06-24 00:07:05,632 epoch 29 - iter 33/39 - loss 0.00000052 - time (sec): 60.45 - samples/sec: 8.74 - lr: 0.000016 - momentum: 0.000000
568
+ 2024-06-24 00:07:10,701 epoch 29 - iter 36/39 - loss 0.00000052 - time (sec): 65.52 - samples/sec: 8.79 - lr: 0.000016 - momentum: 0.000000
569
+ 2024-06-24 00:07:17,290 epoch 29 - iter 39/39 - loss 0.00000051 - time (sec): 72.10 - samples/sec: 8.56 - lr: 0.000016 - momentum: 0.000000
570
+ 2024-06-24 00:07:17,290 ----------------------------------------------------------------------------------------------------
571
+ 2024-06-24 00:07:17,290 EPOCH 29 done: loss 0.0000 - lr: 0.000016
572
+ 2024-06-24 00:07:22,120 DEV : loss 1.7071365118026733 - f1-score (micro avg) 0.8947
573
+ 2024-06-24 00:07:23,742 ----------------------------------------------------------------------------------------------------
574
+ 2024-06-24 00:07:29,222 epoch 30 - iter 3/39 - loss 0.00000009 - time (sec): 5.48 - samples/sec: 8.76 - lr: 0.000016 - momentum: 0.000000
575
+ 2024-06-24 00:07:34,286 epoch 30 - iter 6/39 - loss 0.00000006 - time (sec): 10.54 - samples/sec: 9.11 - lr: 0.000016 - momentum: 0.000000
576
+ 2024-06-24 00:07:42,696 epoch 30 - iter 9/39 - loss 0.00000006 - time (sec): 18.95 - samples/sec: 7.60 - lr: 0.000016 - momentum: 0.000000
577
+ 2024-06-24 00:07:48,003 epoch 30 - iter 12/39 - loss 0.00000166 - time (sec): 24.26 - samples/sec: 7.91 - lr: 0.000015 - momentum: 0.000000
578
+ 2024-06-24 00:07:54,844 epoch 30 - iter 15/39 - loss 0.00000134 - time (sec): 31.10 - samples/sec: 7.72 - lr: 0.000015 - momentum: 0.000000
579
+ 2024-06-24 00:08:01,060 epoch 30 - iter 18/39 - loss 0.00000112 - time (sec): 37.32 - samples/sec: 7.72 - lr: 0.000015 - momentum: 0.000000
580
+ 2024-06-24 00:08:05,774 epoch 30 - iter 21/39 - loss 0.00000097 - time (sec): 42.03 - samples/sec: 7.99 - lr: 0.000015 - momentum: 0.000000
581
+ 2024-06-24 00:08:10,765 epoch 30 - iter 24/39 - loss 0.00000086 - time (sec): 47.02 - samples/sec: 8.17 - lr: 0.000015 - momentum: 0.000000
582
+ 2024-06-24 00:08:15,460 epoch 30 - iter 27/39 - loss 0.00000077 - time (sec): 51.72 - samples/sec: 8.35 - lr: 0.000015 - momentum: 0.000000
583
+ 2024-06-24 00:08:20,307 epoch 30 - iter 30/39 - loss 0.00000070 - time (sec): 56.56 - samples/sec: 8.49 - lr: 0.000015 - momentum: 0.000000
584
+ 2024-06-24 00:08:26,918 epoch 30 - iter 33/39 - loss 0.00000070 - time (sec): 63.18 - samples/sec: 8.36 - lr: 0.000015 - momentum: 0.000000
585
+ 2024-06-24 00:08:31,762 epoch 30 - iter 36/39 - loss 0.00000065 - time (sec): 68.02 - samples/sec: 8.47 - lr: 0.000015 - momentum: 0.000000
586
+ 2024-06-24 00:08:35,864 epoch 30 - iter 39/39 - loss 0.00000061 - time (sec): 72.12 - samples/sec: 8.56 - lr: 0.000014 - momentum: 0.000000
587
+ 2024-06-24 00:08:35,864 ----------------------------------------------------------------------------------------------------
588
+ 2024-06-24 00:08:35,865 EPOCH 30 done: loss 0.0000 - lr: 0.000014
589
+ 2024-06-24 00:08:40,738 DEV : loss 1.7021454572677612 - f1-score (micro avg) 0.8947
590
+ 2024-06-24 00:08:42,445 ----------------------------------------------------------------------------------------------------
591
+ 2024-06-24 00:08:48,744 epoch 31 - iter 3/39 - loss 0.00000041 - time (sec): 6.30 - samples/sec: 7.62 - lr: 0.000014 - momentum: 0.000000
592
+ 2024-06-24 00:08:54,327 epoch 31 - iter 6/39 - loss 0.00000190 - time (sec): 11.88 - samples/sec: 8.08 - lr: 0.000014 - momentum: 0.000000
593
+ 2024-06-24 00:09:00,788 epoch 31 - iter 9/39 - loss 0.00000132 - time (sec): 18.34 - samples/sec: 7.85 - lr: 0.000014 - momentum: 0.000000
594
+ 2024-06-24 00:09:05,605 epoch 31 - iter 12/39 - loss 0.00000100 - time (sec): 23.16 - samples/sec: 8.29 - lr: 0.000014 - momentum: 0.000000
595
+ 2024-06-24 00:09:12,328 epoch 31 - iter 15/39 - loss 0.00000092 - time (sec): 29.88 - samples/sec: 8.03 - lr: 0.000014 - momentum: 0.000000
596
+ 2024-06-24 00:09:16,992 epoch 31 - iter 18/39 - loss 0.00000078 - time (sec): 34.55 - samples/sec: 8.34 - lr: 0.000014 - momentum: 0.000000
597
+ 2024-06-24 00:09:21,873 epoch 31 - iter 21/39 - loss 0.00000068 - time (sec): 39.43 - samples/sec: 8.52 - lr: 0.000014 - momentum: 0.000000
598
+ 2024-06-24 00:09:27,853 epoch 31 - iter 24/39 - loss 0.00000063 - time (sec): 45.41 - samples/sec: 8.46 - lr: 0.000014 - momentum: 0.000000
599
+ 2024-06-24 00:09:32,856 epoch 31 - iter 27/39 - loss 0.00000066 - time (sec): 50.41 - samples/sec: 8.57 - lr: 0.000014 - momentum: 0.000000
600
+ 2024-06-24 00:09:37,731 epoch 31 - iter 30/39 - loss 0.00000063 - time (sec): 55.28 - samples/sec: 8.68 - lr: 0.000013 - momentum: 0.000000
601
+ 2024-06-24 00:09:42,690 epoch 31 - iter 33/39 - loss 0.00000059 - time (sec): 60.24 - samples/sec: 8.76 - lr: 0.000013 - momentum: 0.000000
602
+ 2024-06-24 00:09:48,699 epoch 31 - iter 36/39 - loss 0.00000056 - time (sec): 66.25 - samples/sec: 8.69 - lr: 0.000013 - momentum: 0.000000
603
+ 2024-06-24 00:09:54,531 epoch 31 - iter 39/39 - loss 0.00000053 - time (sec): 72.08 - samples/sec: 8.56 - lr: 0.000013 - momentum: 0.000000
604
+ 2024-06-24 00:09:54,532 ----------------------------------------------------------------------------------------------------
605
+ 2024-06-24 00:09:54,532 EPOCH 31 done: loss 0.0000 - lr: 0.000013
606
+ 2024-06-24 00:09:59,362 DEV : loss 1.6980420351028442 - f1-score (micro avg) 0.8947
607
+ 2024-06-24 00:10:00,982 ----------------------------------------------------------------------------------------------------
608
+ 2024-06-24 00:10:07,046 epoch 32 - iter 3/39 - loss 0.00000006 - time (sec): 6.06 - samples/sec: 7.92 - lr: 0.000013 - momentum: 0.000000
609
+ 2024-06-24 00:10:11,803 epoch 32 - iter 6/39 - loss 0.00000005 - time (sec): 10.82 - samples/sec: 8.87 - lr: 0.000013 - momentum: 0.000000
610
+ 2024-06-24 00:10:17,707 epoch 32 - iter 9/39 - loss 0.00000008 - time (sec): 16.72 - samples/sec: 8.61 - lr: 0.000013 - momentum: 0.000000
611
+ 2024-06-24 00:10:22,746 epoch 32 - iter 12/39 - loss 0.00000009 - time (sec): 21.76 - samples/sec: 8.82 - lr: 0.000013 - momentum: 0.000000
612
+ 2024-06-24 00:10:27,450 epoch 32 - iter 15/39 - loss 0.00000008 - time (sec): 26.47 - samples/sec: 9.07 - lr: 0.000013 - momentum: 0.000000
613
+ 2024-06-24 00:10:33,850 epoch 32 - iter 18/39 - loss 0.00000007 - time (sec): 32.87 - samples/sec: 8.76 - lr: 0.000012 - momentum: 0.000000
614
+ 2024-06-24 00:10:39,384 epoch 32 - iter 21/39 - loss 0.00000008 - time (sec): 38.40 - samples/sec: 8.75 - lr: 0.000012 - momentum: 0.000000
615
+ 2024-06-24 00:10:44,361 epoch 32 - iter 24/39 - loss 0.00000011 - time (sec): 43.38 - samples/sec: 8.85 - lr: 0.000012 - momentum: 0.000000
616
+ 2024-06-24 00:10:50,858 epoch 32 - iter 27/39 - loss 0.00000011 - time (sec): 49.87 - samples/sec: 8.66 - lr: 0.000012 - momentum: 0.000000
617
+ 2024-06-24 00:10:55,639 epoch 32 - iter 30/39 - loss 0.00000013 - time (sec): 54.66 - samples/sec: 8.78 - lr: 0.000012 - momentum: 0.000000
618
+ 2024-06-24 00:11:02,190 epoch 32 - iter 33/39 - loss 0.00000012 - time (sec): 61.21 - samples/sec: 8.63 - lr: 0.000012 - momentum: 0.000000
619
+ 2024-06-24 00:11:07,484 epoch 32 - iter 36/39 - loss 0.00000012 - time (sec): 66.50 - samples/sec: 8.66 - lr: 0.000012 - momentum: 0.000000
620
+ 2024-06-24 00:11:13,239 epoch 32 - iter 39/39 - loss 0.00000012 - time (sec): 72.26 - samples/sec: 8.54 - lr: 0.000012 - momentum: 0.000000
621
+ 2024-06-24 00:11:13,240 ----------------------------------------------------------------------------------------------------
622
+ 2024-06-24 00:11:13,240 EPOCH 32 done: loss 0.0000 - lr: 0.000012
623
+ 2024-06-24 00:11:18,078 DEV : loss 1.6986628770828247 - f1-score (micro avg) 0.8947
624
+ 2024-06-24 00:11:19,773 ----------------------------------------------------------------------------------------------------
625
+ 2024-06-24 00:11:24,783 epoch 33 - iter 3/39 - loss 0.00000010 - time (sec): 5.01 - samples/sec: 9.58 - lr: 0.000012 - momentum: 0.000000
626
+ 2024-06-24 00:11:30,965 epoch 33 - iter 6/39 - loss 0.00000014 - time (sec): 11.19 - samples/sec: 8.58 - lr: 0.000011 - momentum: 0.000000
627
+ 2024-06-24 00:11:35,856 epoch 33 - iter 9/39 - loss 0.00000017 - time (sec): 16.08 - samples/sec: 8.95 - lr: 0.000011 - momentum: 0.000000
628
+ 2024-06-24 00:11:40,951 epoch 33 - iter 12/39 - loss 0.00000013 - time (sec): 21.18 - samples/sec: 9.07 - lr: 0.000011 - momentum: 0.000000
629
+ 2024-06-24 00:11:47,505 epoch 33 - iter 15/39 - loss 0.00000011 - time (sec): 27.73 - samples/sec: 8.65 - lr: 0.000011 - momentum: 0.000000
630
+ 2024-06-24 00:11:53,935 epoch 33 - iter 18/39 - loss 0.00000010 - time (sec): 34.16 - samples/sec: 8.43 - lr: 0.000011 - momentum: 0.000000
631
+ 2024-06-24 00:11:59,165 epoch 33 - iter 21/39 - loss 0.00000010 - time (sec): 39.39 - samples/sec: 8.53 - lr: 0.000011 - momentum: 0.000000
632
+ 2024-06-24 00:12:05,219 epoch 33 - iter 24/39 - loss 0.00000012 - time (sec): 45.44 - samples/sec: 8.45 - lr: 0.000011 - momentum: 0.000000
633
+ 2024-06-24 00:12:10,844 epoch 33 - iter 27/39 - loss 0.00000017 - time (sec): 51.07 - samples/sec: 8.46 - lr: 0.000011 - momentum: 0.000000
634
+ 2024-06-24 00:12:15,467 epoch 33 - iter 30/39 - loss 0.00000016 - time (sec): 55.69 - samples/sec: 8.62 - lr: 0.000011 - momentum: 0.000000
635
+ 2024-06-24 00:12:22,880 epoch 33 - iter 33/39 - loss 0.00000015 - time (sec): 63.11 - samples/sec: 8.37 - lr: 0.000011 - momentum: 0.000000
636
+ 2024-06-24 00:12:27,673 epoch 33 - iter 36/39 - loss 0.00000036 - time (sec): 67.90 - samples/sec: 8.48 - lr: 0.000010 - momentum: 0.000000
637
+ 2024-06-24 00:12:31,856 epoch 33 - iter 39/39 - loss 0.00000040 - time (sec): 72.08 - samples/sec: 8.56 - lr: 0.000010 - momentum: 0.000000
638
+ 2024-06-24 00:12:31,856 ----------------------------------------------------------------------------------------------------
639
+ 2024-06-24 00:12:31,856 EPOCH 33 done: loss 0.0000 - lr: 0.000010
640
+ 2024-06-24 00:12:36,744 DEV : loss 1.698986291885376 - f1-score (micro avg) 0.8947
641
+ 2024-06-24 00:12:38,450 ----------------------------------------------------------------------------------------------------
642
+ 2024-06-24 00:12:44,875 epoch 34 - iter 3/39 - loss 0.00000021 - time (sec): 6.42 - samples/sec: 7.47 - lr: 0.000010 - momentum: 0.000000
643
+ 2024-06-24 00:12:49,539 epoch 34 - iter 6/39 - loss 0.00000018 - time (sec): 11.09 - samples/sec: 8.66 - lr: 0.000010 - momentum: 0.000000
644
+ 2024-06-24 00:12:54,424 epoch 34 - iter 9/39 - loss 0.00000081 - time (sec): 15.97 - samples/sec: 9.02 - lr: 0.000010 - momentum: 0.000000
645
+ 2024-06-24 00:13:00,509 epoch 34 - iter 12/39 - loss 0.00000062 - time (sec): 22.06 - samples/sec: 8.70 - lr: 0.000010 - momentum: 0.000000
646
+ 2024-06-24 00:13:06,842 epoch 34 - iter 15/39 - loss 0.00000063 - time (sec): 28.39 - samples/sec: 8.45 - lr: 0.000010 - momentum: 0.000000
647
+ 2024-06-24 00:13:11,704 epoch 34 - iter 18/39 - loss 0.00000054 - time (sec): 33.25 - samples/sec: 8.66 - lr: 0.000010 - momentum: 0.000000
648
+ 2024-06-24 00:13:17,655 epoch 34 - iter 21/39 - loss 0.00000048 - time (sec): 39.20 - samples/sec: 8.57 - lr: 0.000010 - momentum: 0.000000
649
+ 2024-06-24 00:13:22,770 epoch 34 - iter 24/39 - loss 0.00000042 - time (sec): 44.32 - samples/sec: 8.66 - lr: 0.000009 - momentum: 0.000000
650
+ 2024-06-24 00:13:29,291 epoch 34 - iter 27/39 - loss 0.00000043 - time (sec): 50.84 - samples/sec: 8.50 - lr: 0.000009 - momentum: 0.000000
651
+ 2024-06-24 00:13:35,129 epoch 34 - iter 30/39 - loss 0.00000041 - time (sec): 56.68 - samples/sec: 8.47 - lr: 0.000009 - momentum: 0.000000
652
+ 2024-06-24 00:13:40,347 epoch 34 - iter 33/39 - loss 0.00000041 - time (sec): 61.90 - samples/sec: 8.53 - lr: 0.000009 - momentum: 0.000000
653
+ 2024-06-24 00:13:46,088 epoch 34 - iter 36/39 - loss 0.00000038 - time (sec): 67.64 - samples/sec: 8.52 - lr: 0.000009 - momentum: 0.000000
654
+ 2024-06-24 00:13:50,488 epoch 34 - iter 39/39 - loss 0.00000038 - time (sec): 72.04 - samples/sec: 8.57 - lr: 0.000009 - momentum: 0.000000
655
+ 2024-06-24 00:13:50,489 ----------------------------------------------------------------------------------------------------
656
+ 2024-06-24 00:13:50,489 EPOCH 34 done: loss 0.0000 - lr: 0.000009
657
+ 2024-06-24 00:13:55,272 DEV : loss 1.6952990293502808 - f1-score (micro avg) 0.8947
658
+ 2024-06-24 00:13:56,989 ----------------------------------------------------------------------------------------------------
659
+ 2024-06-24 00:14:02,600 epoch 35 - iter 3/39 - loss 0.00000542 - time (sec): 5.61 - samples/sec: 8.56 - lr: 0.000009 - momentum: 0.000000
660
+ 2024-06-24 00:14:07,465 epoch 35 - iter 6/39 - loss 0.00000277 - time (sec): 10.48 - samples/sec: 9.16 - lr: 0.000009 - momentum: 0.000000
661
+ 2024-06-24 00:14:13,116 epoch 35 - iter 9/39 - loss 0.00000187 - time (sec): 16.13 - samples/sec: 8.93 - lr: 0.000009 - momentum: 0.000000
662
+ 2024-06-24 00:14:18,093 epoch 35 - iter 12/39 - loss 0.00000141 - time (sec): 21.10 - samples/sec: 9.10 - lr: 0.000009 - momentum: 0.000000
663
+ 2024-06-24 00:14:22,728 epoch 35 - iter 15/39 - loss 0.00000113 - time (sec): 25.74 - samples/sec: 9.32 - lr: 0.000008 - momentum: 0.000000
664
+ 2024-06-24 00:14:27,596 epoch 35 - iter 18/39 - loss 0.00000100 - time (sec): 30.61 - samples/sec: 9.41 - lr: 0.000008 - momentum: 0.000000
665
+ 2024-06-24 00:14:33,535 epoch 35 - iter 21/39 - loss 0.00000087 - time (sec): 36.54 - samples/sec: 9.19 - lr: 0.000008 - momentum: 0.000000
666
+ 2024-06-24 00:14:41,102 epoch 35 - iter 24/39 - loss 0.00000076 - time (sec): 44.11 - samples/sec: 8.71 - lr: 0.000008 - momentum: 0.000000
667
+ 2024-06-24 00:14:45,906 epoch 35 - iter 27/39 - loss 0.00000068 - time (sec): 48.92 - samples/sec: 8.83 - lr: 0.000008 - momentum: 0.000000
668
+ 2024-06-24 00:14:52,195 epoch 35 - iter 30/39 - loss 0.00000062 - time (sec): 55.20 - samples/sec: 8.69 - lr: 0.000008 - momentum: 0.000000
669
+ 2024-06-24 00:14:58,255 epoch 35 - iter 33/39 - loss 0.00000057 - time (sec): 61.26 - samples/sec: 8.62 - lr: 0.000008 - momentum: 0.000000
670
+ 2024-06-24 00:15:05,341 epoch 35 - iter 36/39 - loss 0.00000052 - time (sec): 68.35 - samples/sec: 8.43 - lr: 0.000008 - momentum: 0.000000
671
+ 2024-06-24 00:15:09,398 epoch 35 - iter 39/39 - loss 0.00000050 - time (sec): 72.41 - samples/sec: 8.52 - lr: 0.000008 - momentum: 0.000000
672
+ 2024-06-24 00:15:09,399 ----------------------------------------------------------------------------------------------------
673
+ 2024-06-24 00:15:09,399 EPOCH 35 done: loss 0.0000 - lr: 0.000008
674
+ 2024-06-24 00:15:14,284 DEV : loss 1.7006655931472778 - f1-score (micro avg) 0.8947
675
+ 2024-06-24 00:15:16,011 ----------------------------------------------------------------------------------------------------
676
+ 2024-06-24 00:15:20,891 epoch 36 - iter 3/39 - loss 0.00000127 - time (sec): 4.88 - samples/sec: 9.84 - lr: 0.000007 - momentum: 0.000000
677
+ 2024-06-24 00:15:26,005 epoch 36 - iter 6/39 - loss 0.00000069 - time (sec): 9.99 - samples/sec: 9.61 - lr: 0.000007 - momentum: 0.000000
678
+ 2024-06-24 00:15:30,853 epoch 36 - iter 9/39 - loss 0.00000053 - time (sec): 14.84 - samples/sec: 9.70 - lr: 0.000007 - momentum: 0.000000
679
+ 2024-06-24 00:15:36,842 epoch 36 - iter 12/39 - loss 0.00000041 - time (sec): 20.83 - samples/sec: 9.22 - lr: 0.000007 - momentum: 0.000000
680
+ 2024-06-24 00:15:44,294 epoch 36 - iter 15/39 - loss 0.00000037 - time (sec): 28.28 - samples/sec: 8.49 - lr: 0.000007 - momentum: 0.000000
681
+ 2024-06-24 00:15:49,327 epoch 36 - iter 18/39 - loss 0.00000033 - time (sec): 33.32 - samples/sec: 8.64 - lr: 0.000007 - momentum: 0.000000
682
+ 2024-06-24 00:15:54,236 epoch 36 - iter 21/39 - loss 0.00000028 - time (sec): 38.22 - samples/sec: 8.79 - lr: 0.000007 - momentum: 0.000000
683
+ 2024-06-24 00:16:00,296 epoch 36 - iter 24/39 - loss 0.00000026 - time (sec): 44.28 - samples/sec: 8.67 - lr: 0.000007 - momentum: 0.000000
684
+ 2024-06-24 00:16:06,692 epoch 36 - iter 27/39 - loss 0.00000026 - time (sec): 50.68 - samples/sec: 8.52 - lr: 0.000007 - momentum: 0.000000
685
+ 2024-06-24 00:16:11,897 epoch 36 - iter 30/39 - loss 0.00000024 - time (sec): 55.89 - samples/sec: 8.59 - lr: 0.000007 - momentum: 0.000000
686
+ 2024-06-24 00:16:17,672 epoch 36 - iter 33/39 - loss 0.00000022 - time (sec): 61.66 - samples/sec: 8.56 - lr: 0.000006 - momentum: 0.000000
687
+ 2024-06-24 00:16:23,749 epoch 36 - iter 36/39 - loss 0.00000021 - time (sec): 67.74 - samples/sec: 8.50 - lr: 0.000006 - momentum: 0.000000
688
+ 2024-06-24 00:16:28,163 epoch 36 - iter 39/39 - loss 0.00000020 - time (sec): 72.15 - samples/sec: 8.55 - lr: 0.000006 - momentum: 0.000000
689
+ 2024-06-24 00:16:28,164 ----------------------------------------------------------------------------------------------------
690
+ 2024-06-24 00:16:28,164 EPOCH 36 done: loss 0.0000 - lr: 0.000006
691
+ 2024-06-24 00:16:32,993 DEV : loss 1.7021197080612183 - f1-score (micro avg) 0.8947
692
+ 2024-06-24 00:16:34,685 ----------------------------------------------------------------------------------------------------
693
+ 2024-06-24 00:16:40,901 epoch 37 - iter 3/39 - loss 0.00000003 - time (sec): 6.22 - samples/sec: 7.72 - lr: 0.000006 - momentum: 0.000000
694
+ 2024-06-24 00:16:45,576 epoch 37 - iter 6/39 - loss 0.00000003 - time (sec): 10.89 - samples/sec: 8.81 - lr: 0.000006 - momentum: 0.000000
695
+ 2024-06-24 00:16:50,468 epoch 37 - iter 9/39 - loss 0.00000009 - time (sec): 15.78 - samples/sec: 9.12 - lr: 0.000006 - momentum: 0.000000
696
+ 2024-06-24 00:16:55,105 epoch 37 - iter 12/39 - loss 0.00000017 - time (sec): 20.42 - samples/sec: 9.40 - lr: 0.000006 - momentum: 0.000000
697
+ 2024-06-24 00:17:00,241 epoch 37 - iter 15/39 - loss 0.00000014 - time (sec): 25.55 - samples/sec: 9.39 - lr: 0.000006 - momentum: 0.000000
698
+ 2024-06-24 00:17:05,538 epoch 37 - iter 18/39 - loss 0.00000013 - time (sec): 30.85 - samples/sec: 9.33 - lr: 0.000006 - momentum: 0.000000
699
+ 2024-06-24 00:17:10,431 epoch 37 - iter 21/39 - loss 0.00000012 - time (sec): 35.75 - samples/sec: 9.40 - lr: 0.000005 - momentum: 0.000000
700
+ 2024-06-24 00:17:15,323 epoch 37 - iter 24/39 - loss 0.00000011 - time (sec): 40.64 - samples/sec: 9.45 - lr: 0.000005 - momentum: 0.000000
701
+ 2024-06-24 00:17:20,272 epoch 37 - iter 27/39 - loss 0.00000015 - time (sec): 45.59 - samples/sec: 9.48 - lr: 0.000005 - momentum: 0.000000
702
+ 2024-06-24 00:17:25,225 epoch 37 - iter 30/39 - loss 0.00000014 - time (sec): 50.54 - samples/sec: 9.50 - lr: 0.000005 - momentum: 0.000000
703
+ 2024-06-24 00:17:34,109 epoch 37 - iter 33/39 - loss 0.00000014 - time (sec): 59.42 - samples/sec: 8.89 - lr: 0.000005 - momentum: 0.000000
704
+ 2024-06-24 00:17:41,163 epoch 37 - iter 36/39 - loss 0.00000014 - time (sec): 66.48 - samples/sec: 8.66 - lr: 0.000005 - momentum: 0.000000
705
+ 2024-06-24 00:17:47,235 epoch 37 - iter 39/39 - loss 0.00000014 - time (sec): 72.55 - samples/sec: 8.50 - lr: 0.000005 - momentum: 0.000000
706
+ 2024-06-24 00:17:47,236 ----------------------------------------------------------------------------------------------------
707
+ 2024-06-24 00:17:47,236 EPOCH 37 done: loss 0.0000 - lr: 0.000005
708
+ 2024-06-24 00:17:51,949 DEV : loss 1.702373743057251 - f1-score (micro avg) 0.8947
709
+ 2024-06-24 00:17:53,691 ----------------------------------------------------------------------------------------------------
710
+ 2024-06-24 00:17:59,399 epoch 38 - iter 3/39 - loss 0.00000261 - time (sec): 5.71 - samples/sec: 8.41 - lr: 0.000005 - momentum: 0.000000
711
+ 2024-06-24 00:18:04,191 epoch 38 - iter 6/39 - loss 0.00000132 - time (sec): 10.50 - samples/sec: 9.14 - lr: 0.000005 - momentum: 0.000000
712
+ 2024-06-24 00:18:10,279 epoch 38 - iter 9/39 - loss 0.00000089 - time (sec): 16.59 - samples/sec: 8.68 - lr: 0.000005 - momentum: 0.000000
713
+ 2024-06-24 00:18:15,059 epoch 38 - iter 12/39 - loss 0.00000069 - time (sec): 21.37 - samples/sec: 8.99 - lr: 0.000004 - momentum: 0.000000
714
+ 2024-06-24 00:18:22,574 epoch 38 - iter 15/39 - loss 0.00000059 - time (sec): 28.88 - samples/sec: 8.31 - lr: 0.000004 - momentum: 0.000000
715
+ 2024-06-24 00:18:27,280 epoch 38 - iter 18/39 - loss 0.00000050 - time (sec): 33.59 - samples/sec: 8.57 - lr: 0.000004 - momentum: 0.000000
716
+ 2024-06-24 00:18:34,816 epoch 38 - iter 21/39 - loss 0.00000048 - time (sec): 41.12 - samples/sec: 8.17 - lr: 0.000004 - momentum: 0.000000
717
+ 2024-06-24 00:18:39,469 epoch 38 - iter 24/39 - loss 0.00000042 - time (sec): 45.78 - samples/sec: 8.39 - lr: 0.000004 - momentum: 0.000000
718
+ 2024-06-24 00:18:45,653 epoch 38 - iter 27/39 - loss 0.00000041 - time (sec): 51.96 - samples/sec: 8.31 - lr: 0.000004 - momentum: 0.000000
719
+ 2024-06-24 00:18:50,547 epoch 38 - iter 30/39 - loss 0.00000037 - time (sec): 56.86 - samples/sec: 8.44 - lr: 0.000004 - momentum: 0.000000
720
+ 2024-06-24 00:18:56,666 epoch 38 - iter 33/39 - loss 0.00000035 - time (sec): 62.97 - samples/sec: 8.38 - lr: 0.000004 - momentum: 0.000000
721
+ 2024-06-24 00:19:01,975 epoch 38 - iter 36/39 - loss 0.00000032 - time (sec): 68.28 - samples/sec: 8.44 - lr: 0.000004 - momentum: 0.000000
722
+ 2024-06-24 00:19:06,188 epoch 38 - iter 39/39 - loss 0.00000030 - time (sec): 72.50 - samples/sec: 8.51 - lr: 0.000003 - momentum: 0.000000
723
+ 2024-06-24 00:19:06,188 ----------------------------------------------------------------------------------------------------
724
+ 2024-06-24 00:19:06,188 EPOCH 38 done: loss 0.0000 - lr: 0.000003
725
+ 2024-06-24 00:19:10,986 DEV : loss 1.7031772136688232 - f1-score (micro avg) 0.8947
726
+ 2024-06-24 00:19:12,580 ----------------------------------------------------------------------------------------------------
727
+ 2024-06-24 00:19:17,415 epoch 39 - iter 3/39 - loss 0.00000003 - time (sec): 4.83 - samples/sec: 9.93 - lr: 0.000003 - momentum: 0.000000
728
+ 2024-06-24 00:19:22,308 epoch 39 - iter 6/39 - loss 0.00000006 - time (sec): 9.73 - samples/sec: 9.87 - lr: 0.000003 - momentum: 0.000000
729
+ 2024-06-24 00:19:28,668 epoch 39 - iter 9/39 - loss 0.00000026 - time (sec): 16.09 - samples/sec: 8.95 - lr: 0.000003 - momentum: 0.000000
730
+ 2024-06-24 00:19:37,048 epoch 39 - iter 12/39 - loss 0.00000021 - time (sec): 24.47 - samples/sec: 7.85 - lr: 0.000003 - momentum: 0.000000
731
+ 2024-06-24 00:19:44,240 epoch 39 - iter 15/39 - loss 0.00000019 - time (sec): 31.66 - samples/sec: 7.58 - lr: 0.000003 - momentum: 0.000000
732
+ 2024-06-24 00:19:49,264 epoch 39 - iter 18/39 - loss 0.00000017 - time (sec): 36.68 - samples/sec: 7.85 - lr: 0.000003 - momentum: 0.000000
733
+ 2024-06-24 00:19:54,357 epoch 39 - iter 21/39 - loss 0.00000015 - time (sec): 41.78 - samples/sec: 8.04 - lr: 0.000003 - momentum: 0.000000
734
+ 2024-06-24 00:19:59,066 epoch 39 - iter 24/39 - loss 0.00000017 - time (sec): 46.49 - samples/sec: 8.26 - lr: 0.000003 - momentum: 0.000000
735
+ 2024-06-24 00:20:03,935 epoch 39 - iter 27/39 - loss 0.00000039 - time (sec): 51.35 - samples/sec: 8.41 - lr: 0.000003 - momentum: 0.000000
736
+ 2024-06-24 00:20:10,405 epoch 39 - iter 30/39 - loss 0.00000036 - time (sec): 57.82 - samples/sec: 8.30 - lr: 0.000002 - momentum: 0.000000
737
+ 2024-06-24 00:20:15,268 epoch 39 - iter 33/39 - loss 0.00000033 - time (sec): 62.69 - samples/sec: 8.42 - lr: 0.000002 - momentum: 0.000000
738
+ 2024-06-24 00:20:20,926 epoch 39 - iter 36/39 - loss 0.00000034 - time (sec): 68.35 - samples/sec: 8.43 - lr: 0.000002 - momentum: 0.000000
739
+ 2024-06-24 00:20:25,040 epoch 39 - iter 39/39 - loss 0.00000032 - time (sec): 72.46 - samples/sec: 8.52 - lr: 0.000002 - momentum: 0.000000
740
+ 2024-06-24 00:20:25,041 ----------------------------------------------------------------------------------------------------
741
+ 2024-06-24 00:20:25,041 EPOCH 39 done: loss 0.0000 - lr: 0.000002
742
+ 2024-06-24 00:20:29,851 DEV : loss 1.7041176557540894 - f1-score (micro avg) 0.8947
743
+ 2024-06-24 00:20:31,571 ----------------------------------------------------------------------------------------------------
744
+ 2024-06-24 00:20:36,431 epoch 40 - iter 3/39 - loss 0.00000288 - time (sec): 4.86 - samples/sec: 9.88 - lr: 0.000002 - momentum: 0.000000
745
+ 2024-06-24 00:20:43,066 epoch 40 - iter 6/39 - loss 0.00000146 - time (sec): 11.49 - samples/sec: 8.35 - lr: 0.000002 - momentum: 0.000000
746
+ 2024-06-24 00:20:48,875 epoch 40 - iter 9/39 - loss 0.00000100 - time (sec): 17.30 - samples/sec: 8.32 - lr: 0.000002 - momentum: 0.000000
747
+ 2024-06-24 00:20:55,648 epoch 40 - iter 12/39 - loss 0.00000078 - time (sec): 24.08 - samples/sec: 7.97 - lr: 0.000002 - momentum: 0.000000
748
+ 2024-06-24 00:21:00,428 epoch 40 - iter 15/39 - loss 0.00000064 - time (sec): 28.86 - samples/sec: 8.32 - lr: 0.000002 - momentum: 0.000000
749
+ 2024-06-24 00:21:05,272 epoch 40 - iter 18/39 - loss 0.00000054 - time (sec): 33.70 - samples/sec: 8.55 - lr: 0.000001 - momentum: 0.000000
750
+ 2024-06-24 00:21:11,236 epoch 40 - iter 21/39 - loss 0.00000047 - time (sec): 39.66 - samples/sec: 8.47 - lr: 0.000001 - momentum: 0.000000
751
+ 2024-06-24 00:21:17,478 epoch 40 - iter 24/39 - loss 0.00000042 - time (sec): 45.91 - samples/sec: 8.37 - lr: 0.000001 - momentum: 0.000000
752
+ 2024-06-24 00:21:22,265 epoch 40 - iter 27/39 - loss 0.00000037 - time (sec): 50.69 - samples/sec: 8.52 - lr: 0.000001 - momentum: 0.000000
753
+ 2024-06-24 00:21:27,415 epoch 40 - iter 30/39 - loss 0.00000034 - time (sec): 55.84 - samples/sec: 8.60 - lr: 0.000001 - momentum: 0.000000
754
+ 2024-06-24 00:21:32,200 epoch 40 - iter 33/39 - loss 0.00000032 - time (sec): 60.63 - samples/sec: 8.71 - lr: 0.000001 - momentum: 0.000000
755
+ 2024-06-24 00:21:38,217 epoch 40 - iter 36/39 - loss 0.00000031 - time (sec): 66.64 - samples/sec: 8.64 - lr: 0.000001 - momentum: 0.000000
756
+ 2024-06-24 00:21:44,225 epoch 40 - iter 39/39 - loss 0.00000030 - time (sec): 72.65 - samples/sec: 8.49 - lr: 0.000001 - momentum: 0.000000
757
+ 2024-06-24 00:21:44,226 ----------------------------------------------------------------------------------------------------
758
+ 2024-06-24 00:21:44,226 EPOCH 40 done: loss 0.0000 - lr: 0.000001
759
+ 2024-06-24 00:21:48,944 DEV : loss 1.7045665979385376 - f1-score (micro avg) 0.8947
760
+ 2024-06-24 00:21:51,063 ----------------------------------------------------------------------------------------------------
761
+ 2024-06-24 00:21:51,064 Testing using last state of model ...
762
+ 2024-06-24 00:21:56,953
763
+ Results:
764
+ - F-score (micro) 0.9367
765
+ - F-score (macro) 0.9177
766
+ - Accuracy 0.9367
767
+
768
+ By class:
769
+ precision recall f1-score support
770
+
771
+ negative 0.9655 0.9492 0.9573 59
772
+ positive 0.8571 0.9000 0.8780 20
773
+
774
+ accuracy 0.9367 79
775
+ macro avg 0.9113 0.9246 0.9177 79
776
+ weighted avg 0.9381 0.9367 0.9372 79
777
+
778
+ 2024-06-24 00:21:56,954 ----------------------------------------------------------------------------------------------------