| 2023-10-15 14:01:36,257 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-15 14:01:36,258 Model: "SequenceTagger( | |
| (embeddings): TransformerWordEmbeddings( | |
| (model): BertModel( | |
| (embeddings): BertEmbeddings( | |
| (word_embeddings): Embedding(32001, 768) | |
| (position_embeddings): Embedding(512, 768) | |
| (token_type_embeddings): Embedding(2, 768) | |
| (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| (encoder): BertEncoder( | |
| (layer): ModuleList( | |
| (0-11): 12 x BertLayer( | |
| (attention): BertAttention( | |
| (self): BertSelfAttention( | |
| (query): Linear(in_features=768, out_features=768, bias=True) | |
| (key): Linear(in_features=768, out_features=768, bias=True) | |
| (value): Linear(in_features=768, out_features=768, bias=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| (output): BertSelfOutput( | |
| (dense): Linear(in_features=768, out_features=768, bias=True) | |
| (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| (intermediate): BertIntermediate( | |
| (dense): Linear(in_features=768, out_features=3072, bias=True) | |
| (intermediate_act_fn): GELUActivation() | |
| ) | |
| (output): BertOutput( | |
| (dense): Linear(in_features=3072, out_features=768, bias=True) | |
| (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| ) | |
| ) | |
| (pooler): BertPooler( | |
| (dense): Linear(in_features=768, out_features=768, bias=True) | |
| (activation): Tanh() | |
| ) | |
| ) | |
| ) | |
| (locked_dropout): LockedDropout(p=0.5) | |
| (linear): Linear(in_features=768, out_features=17, bias=True) | |
| (loss_function): CrossEntropyLoss() | |
| )" | |
| 2023-10-15 14:01:36,258 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-15 14:01:36,258 MultiCorpus: 20847 train + 1123 dev + 3350 test sentences | |
| - NER_HIPE_2022 Corpus: 20847 train + 1123 dev + 3350 test sentences - /root/.flair/datasets/ner_hipe_2022/v2.1/newseye/de/with_doc_seperator | |
| 2023-10-15 14:01:36,258 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-15 14:01:36,258 Train: 20847 sentences | |
| 2023-10-15 14:01:36,258 (train_with_dev=False, train_with_test=False) | |
| 2023-10-15 14:01:36,258 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-15 14:01:36,258 Training Params: | |
| 2023-10-15 14:01:36,258 - learning_rate: "3e-05" | |
| 2023-10-15 14:01:36,258 - mini_batch_size: "8" | |
| 2023-10-15 14:01:36,258 - max_epochs: "10" | |
| 2023-10-15 14:01:36,259 - shuffle: "True" | |
| 2023-10-15 14:01:36,259 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-15 14:01:36,259 Plugins: | |
| 2023-10-15 14:01:36,259 - LinearScheduler | warmup_fraction: '0.1' | |
| 2023-10-15 14:01:36,259 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-15 14:01:36,259 Final evaluation on model from best epoch (best-model.pt) | |
| 2023-10-15 14:01:36,259 - metric: "('micro avg', 'f1-score')" | |
| 2023-10-15 14:01:36,259 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-15 14:01:36,259 Computation: | |
| 2023-10-15 14:01:36,259 - compute on device: cuda:0 | |
| 2023-10-15 14:01:36,259 - embedding storage: none | |
| 2023-10-15 14:01:36,259 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-15 14:01:36,259 Model training base path: "hmbench-newseye/de-dbmdz/bert-base-historic-multilingual-cased-bs8-wsFalse-e10-lr3e-05-poolingfirst-layers-1-crfFalse-2" | |
| 2023-10-15 14:01:36,259 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-15 14:01:36,259 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-15 14:01:55,792 epoch 1 - iter 260/2606 - loss 2.10500958 - time (sec): 19.53 - samples/sec: 1932.41 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-15 14:02:15,076 epoch 1 - iter 520/2606 - loss 1.26983835 - time (sec): 38.82 - samples/sec: 1922.46 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-15 14:02:34,769 epoch 1 - iter 780/2606 - loss 0.94395616 - time (sec): 58.51 - samples/sec: 1956.46 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-15 14:02:53,143 epoch 1 - iter 1040/2606 - loss 0.79513165 - time (sec): 76.88 - samples/sec: 1943.46 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-15 14:03:11,642 epoch 1 - iter 1300/2606 - loss 0.68606228 - time (sec): 95.38 - samples/sec: 1952.23 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-15 14:03:30,437 epoch 1 - iter 1560/2606 - loss 0.61116996 - time (sec): 114.18 - samples/sec: 1953.28 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-15 14:03:49,261 epoch 1 - iter 1820/2606 - loss 0.55490958 - time (sec): 133.00 - samples/sec: 1945.68 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-15 14:04:06,976 epoch 1 - iter 2080/2606 - loss 0.51740975 - time (sec): 150.72 - samples/sec: 1945.69 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-15 14:04:25,979 epoch 1 - iter 2340/2606 - loss 0.47955013 - time (sec): 169.72 - samples/sec: 1946.46 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-15 14:04:44,448 epoch 1 - iter 2600/2606 - loss 0.45046229 - time (sec): 188.19 - samples/sec: 1946.99 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-10-15 14:04:44,960 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-15 14:04:44,960 EPOCH 1 done: loss 0.4501 - lr: 0.000030 | |
| 2023-10-15 14:04:50,762 DEV : loss 0.14003677666187286 - f1-score (micro avg) 0.2844 | |
| 2023-10-15 14:04:50,788 saving best model | |
| 2023-10-15 14:04:51,134 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-15 14:05:09,702 epoch 2 - iter 260/2606 - loss 0.15343561 - time (sec): 18.57 - samples/sec: 1884.69 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-10-15 14:05:28,205 epoch 2 - iter 520/2606 - loss 0.15178841 - time (sec): 37.07 - samples/sec: 1922.84 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-15 14:05:47,186 epoch 2 - iter 780/2606 - loss 0.16502854 - time (sec): 56.05 - samples/sec: 1943.13 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-15 14:06:05,881 epoch 2 - iter 1040/2606 - loss 0.15965107 - time (sec): 74.75 - samples/sec: 1937.79 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-15 14:06:24,879 epoch 2 - iter 1300/2606 - loss 0.15210531 - time (sec): 93.74 - samples/sec: 1938.76 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-15 14:06:44,999 epoch 2 - iter 1560/2606 - loss 0.15153758 - time (sec): 113.86 - samples/sec: 1931.12 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-15 14:07:03,975 epoch 2 - iter 1820/2606 - loss 0.15458329 - time (sec): 132.84 - samples/sec: 1927.42 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-15 14:07:22,929 epoch 2 - iter 2080/2606 - loss 0.15036258 - time (sec): 151.79 - samples/sec: 1939.42 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-15 14:07:41,239 epoch 2 - iter 2340/2606 - loss 0.14805015 - time (sec): 170.10 - samples/sec: 1941.09 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-15 14:07:59,299 epoch 2 - iter 2600/2606 - loss 0.14621051 - time (sec): 188.16 - samples/sec: 1947.42 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-15 14:07:59,743 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-15 14:07:59,743 EPOCH 2 done: loss 0.1462 - lr: 0.000027 | |
| 2023-10-15 14:08:08,774 DEV : loss 0.13364139199256897 - f1-score (micro avg) 0.39 | |
| 2023-10-15 14:08:08,801 saving best model | |
| 2023-10-15 14:08:09,245 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-15 14:08:28,868 epoch 3 - iter 260/2606 - loss 0.09480531 - time (sec): 19.62 - samples/sec: 1974.43 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-15 14:08:48,315 epoch 3 - iter 520/2606 - loss 0.09762294 - time (sec): 39.07 - samples/sec: 1983.56 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-15 14:09:07,080 epoch 3 - iter 780/2606 - loss 0.09675264 - time (sec): 57.83 - samples/sec: 1980.67 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-15 14:09:25,697 epoch 3 - iter 1040/2606 - loss 0.09948955 - time (sec): 76.45 - samples/sec: 1965.21 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-15 14:09:45,450 epoch 3 - iter 1300/2606 - loss 0.09948710 - time (sec): 96.20 - samples/sec: 1957.06 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-15 14:10:03,728 epoch 3 - iter 1560/2606 - loss 0.09994118 - time (sec): 114.48 - samples/sec: 1944.58 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-15 14:10:22,050 epoch 3 - iter 1820/2606 - loss 0.10105418 - time (sec): 132.80 - samples/sec: 1940.74 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-15 14:10:40,160 epoch 3 - iter 2080/2606 - loss 0.10069437 - time (sec): 150.91 - samples/sec: 1941.19 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-15 14:10:59,724 epoch 3 - iter 2340/2606 - loss 0.09900983 - time (sec): 170.48 - samples/sec: 1937.15 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-15 14:11:18,082 epoch 3 - iter 2600/2606 - loss 0.09855936 - time (sec): 188.83 - samples/sec: 1937.91 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-15 14:11:18,766 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-15 14:11:18,767 EPOCH 3 done: loss 0.0983 - lr: 0.000023 | |
| 2023-10-15 14:11:27,767 DEV : loss 0.3090475797653198 - f1-score (micro avg) 0.3401 | |
| 2023-10-15 14:11:27,807 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-15 14:11:47,935 epoch 4 - iter 260/2606 - loss 0.06471452 - time (sec): 20.13 - samples/sec: 1920.58 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-15 14:12:05,741 epoch 4 - iter 520/2606 - loss 0.06762329 - time (sec): 37.93 - samples/sec: 1906.81 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-15 14:12:24,546 epoch 4 - iter 780/2606 - loss 0.06800522 - time (sec): 56.74 - samples/sec: 1930.44 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-15 14:12:42,675 epoch 4 - iter 1040/2606 - loss 0.06657946 - time (sec): 74.87 - samples/sec: 1938.41 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-15 14:13:01,137 epoch 4 - iter 1300/2606 - loss 0.06471875 - time (sec): 93.33 - samples/sec: 1948.71 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-15 14:13:20,193 epoch 4 - iter 1560/2606 - loss 0.06505784 - time (sec): 112.38 - samples/sec: 1951.95 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-15 14:13:38,849 epoch 4 - iter 1820/2606 - loss 0.06630090 - time (sec): 131.04 - samples/sec: 1949.47 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-15 14:13:57,364 epoch 4 - iter 2080/2606 - loss 0.06697785 - time (sec): 149.56 - samples/sec: 1944.52 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-15 14:14:17,007 epoch 4 - iter 2340/2606 - loss 0.06760635 - time (sec): 169.20 - samples/sec: 1944.05 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-15 14:14:36,161 epoch 4 - iter 2600/2606 - loss 0.06815817 - time (sec): 188.35 - samples/sec: 1946.62 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-15 14:14:36,569 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-15 14:14:36,570 EPOCH 4 done: loss 0.0681 - lr: 0.000020 | |
| 2023-10-15 14:14:45,494 DEV : loss 0.24350780248641968 - f1-score (micro avg) 0.3667 | |
| 2023-10-15 14:14:45,521 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-15 14:15:03,951 epoch 5 - iter 260/2606 - loss 0.04722609 - time (sec): 18.43 - samples/sec: 1993.69 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-15 14:15:24,644 epoch 5 - iter 520/2606 - loss 0.04908254 - time (sec): 39.12 - samples/sec: 1995.90 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-15 14:15:43,022 epoch 5 - iter 780/2606 - loss 0.04697712 - time (sec): 57.50 - samples/sec: 1977.43 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-15 14:16:02,706 epoch 5 - iter 1040/2606 - loss 0.04721646 - time (sec): 77.18 - samples/sec: 1973.46 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-15 14:16:20,741 epoch 5 - iter 1300/2606 - loss 0.04714736 - time (sec): 95.22 - samples/sec: 1971.98 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-15 14:16:40,230 epoch 5 - iter 1560/2606 - loss 0.04707598 - time (sec): 114.71 - samples/sec: 1967.68 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-15 14:16:59,025 epoch 5 - iter 1820/2606 - loss 0.04670234 - time (sec): 133.50 - samples/sec: 1951.10 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-15 14:17:17,213 epoch 5 - iter 2080/2606 - loss 0.04877738 - time (sec): 151.69 - samples/sec: 1949.95 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-15 14:17:36,115 epoch 5 - iter 2340/2606 - loss 0.05008815 - time (sec): 170.59 - samples/sec: 1954.53 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-15 14:17:53,766 epoch 5 - iter 2600/2606 - loss 0.05049142 - time (sec): 188.24 - samples/sec: 1948.52 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-15 14:17:54,153 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-15 14:17:54,153 EPOCH 5 done: loss 0.0505 - lr: 0.000017 | |
| 2023-10-15 14:18:03,078 DEV : loss 0.33405596017837524 - f1-score (micro avg) 0.3807 | |
| 2023-10-15 14:18:03,104 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-15 14:18:22,812 epoch 6 - iter 260/2606 - loss 0.02891067 - time (sec): 19.71 - samples/sec: 1956.11 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-15 14:18:40,995 epoch 6 - iter 520/2606 - loss 0.03662193 - time (sec): 37.89 - samples/sec: 1964.56 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-15 14:18:59,480 epoch 6 - iter 780/2606 - loss 0.03599884 - time (sec): 56.37 - samples/sec: 1978.28 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-15 14:19:17,797 epoch 6 - iter 1040/2606 - loss 0.03753291 - time (sec): 74.69 - samples/sec: 1951.04 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-15 14:19:37,287 epoch 6 - iter 1300/2606 - loss 0.03732199 - time (sec): 94.18 - samples/sec: 1952.12 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-15 14:19:56,296 epoch 6 - iter 1560/2606 - loss 0.03809148 - time (sec): 113.19 - samples/sec: 1955.68 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-15 14:20:16,435 epoch 6 - iter 1820/2606 - loss 0.03657832 - time (sec): 133.33 - samples/sec: 1960.96 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-15 14:20:34,252 epoch 6 - iter 2080/2606 - loss 0.03754956 - time (sec): 151.15 - samples/sec: 1955.27 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-15 14:20:52,808 epoch 6 - iter 2340/2606 - loss 0.03695265 - time (sec): 169.70 - samples/sec: 1952.85 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-15 14:21:11,112 epoch 6 - iter 2600/2606 - loss 0.03678499 - time (sec): 188.01 - samples/sec: 1949.06 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-15 14:21:11,590 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-15 14:21:11,591 EPOCH 6 done: loss 0.0367 - lr: 0.000013 | |
| 2023-10-15 14:21:20,530 DEV : loss 0.3696856200695038 - f1-score (micro avg) 0.3708 | |
| 2023-10-15 14:21:20,557 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-15 14:21:38,363 epoch 7 - iter 260/2606 - loss 0.02251214 - time (sec): 17.81 - samples/sec: 1894.53 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-15 14:21:56,785 epoch 7 - iter 520/2606 - loss 0.02776332 - time (sec): 36.23 - samples/sec: 1912.76 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-15 14:22:16,268 epoch 7 - iter 780/2606 - loss 0.02781888 - time (sec): 55.71 - samples/sec: 1940.00 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-15 14:22:34,320 epoch 7 - iter 1040/2606 - loss 0.02918939 - time (sec): 73.76 - samples/sec: 1932.80 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-15 14:22:52,187 epoch 7 - iter 1300/2606 - loss 0.02885109 - time (sec): 91.63 - samples/sec: 1929.34 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-15 14:23:10,587 epoch 7 - iter 1560/2606 - loss 0.02859748 - time (sec): 110.03 - samples/sec: 1942.85 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-15 14:23:29,589 epoch 7 - iter 1820/2606 - loss 0.02842582 - time (sec): 129.03 - samples/sec: 1943.10 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-15 14:23:48,843 epoch 7 - iter 2080/2606 - loss 0.02738935 - time (sec): 148.29 - samples/sec: 1953.11 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-15 14:24:08,024 epoch 7 - iter 2340/2606 - loss 0.02673557 - time (sec): 167.47 - samples/sec: 1961.27 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-15 14:24:27,295 epoch 7 - iter 2600/2606 - loss 0.02752743 - time (sec): 186.74 - samples/sec: 1959.26 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-15 14:24:28,085 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-15 14:24:28,086 EPOCH 7 done: loss 0.0274 - lr: 0.000010 | |
| 2023-10-15 14:24:36,409 DEV : loss 0.40790677070617676 - f1-score (micro avg) 0.3719 | |
| 2023-10-15 14:24:36,438 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-15 14:24:55,407 epoch 8 - iter 260/2606 - loss 0.01291656 - time (sec): 18.97 - samples/sec: 2010.97 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-15 14:25:15,266 epoch 8 - iter 520/2606 - loss 0.01561056 - time (sec): 38.83 - samples/sec: 1931.01 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-15 14:25:33,534 epoch 8 - iter 780/2606 - loss 0.01711152 - time (sec): 57.10 - samples/sec: 1900.24 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-15 14:25:52,324 epoch 8 - iter 1040/2606 - loss 0.01692317 - time (sec): 75.88 - samples/sec: 1910.09 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-15 14:26:10,343 epoch 8 - iter 1300/2606 - loss 0.01745508 - time (sec): 93.90 - samples/sec: 1904.76 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-15 14:26:29,544 epoch 8 - iter 1560/2606 - loss 0.01789181 - time (sec): 113.11 - samples/sec: 1905.43 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-15 14:26:48,970 epoch 8 - iter 1820/2606 - loss 0.01759359 - time (sec): 132.53 - samples/sec: 1929.92 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-15 14:27:08,447 epoch 8 - iter 2080/2606 - loss 0.01988694 - time (sec): 152.01 - samples/sec: 1934.62 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-15 14:27:26,703 epoch 8 - iter 2340/2606 - loss 0.01975246 - time (sec): 170.26 - samples/sec: 1935.81 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-15 14:27:45,522 epoch 8 - iter 2600/2606 - loss 0.01936912 - time (sec): 189.08 - samples/sec: 1938.14 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-15 14:27:45,948 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-15 14:27:45,948 EPOCH 8 done: loss 0.0193 - lr: 0.000007 | |
| 2023-10-15 14:27:54,258 DEV : loss 0.47605660557746887 - f1-score (micro avg) 0.3764 | |
| 2023-10-15 14:27:54,286 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-15 14:28:12,090 epoch 9 - iter 260/2606 - loss 0.01344739 - time (sec): 17.80 - samples/sec: 1944.75 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-15 14:28:30,090 epoch 9 - iter 520/2606 - loss 0.01392440 - time (sec): 35.80 - samples/sec: 1912.57 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-15 14:28:49,788 epoch 9 - iter 780/2606 - loss 0.01322424 - time (sec): 55.50 - samples/sec: 1949.28 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-15 14:29:08,912 epoch 9 - iter 1040/2606 - loss 0.01368991 - time (sec): 74.62 - samples/sec: 1945.75 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-15 14:29:29,116 epoch 9 - iter 1300/2606 - loss 0.01353773 - time (sec): 94.83 - samples/sec: 1930.19 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-15 14:29:48,188 epoch 9 - iter 1560/2606 - loss 0.01447917 - time (sec): 113.90 - samples/sec: 1929.00 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-15 14:30:07,028 epoch 9 - iter 1820/2606 - loss 0.01464400 - time (sec): 132.74 - samples/sec: 1938.67 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-15 14:30:25,120 epoch 9 - iter 2080/2606 - loss 0.01479487 - time (sec): 150.83 - samples/sec: 1947.30 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-15 14:30:43,960 epoch 9 - iter 2340/2606 - loss 0.01446972 - time (sec): 169.67 - samples/sec: 1948.17 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-15 14:31:02,704 epoch 9 - iter 2600/2606 - loss 0.01440697 - time (sec): 188.42 - samples/sec: 1948.19 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-15 14:31:02,988 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-15 14:31:02,988 EPOCH 9 done: loss 0.0144 - lr: 0.000003 | |
| 2023-10-15 14:31:11,206 DEV : loss 0.5070585012435913 - f1-score (micro avg) 0.357 | |
| 2023-10-15 14:31:11,233 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-15 14:31:29,933 epoch 10 - iter 260/2606 - loss 0.00817533 - time (sec): 18.70 - samples/sec: 1976.58 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-15 14:31:48,831 epoch 10 - iter 520/2606 - loss 0.01083697 - time (sec): 37.60 - samples/sec: 1963.51 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-15 14:32:08,276 epoch 10 - iter 780/2606 - loss 0.01055400 - time (sec): 57.04 - samples/sec: 1983.88 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-15 14:32:26,967 epoch 10 - iter 1040/2606 - loss 0.00978576 - time (sec): 75.73 - samples/sec: 1979.43 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-15 14:32:44,756 epoch 10 - iter 1300/2606 - loss 0.00974007 - time (sec): 93.52 - samples/sec: 1969.25 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-15 14:33:03,283 epoch 10 - iter 1560/2606 - loss 0.01014539 - time (sec): 112.05 - samples/sec: 1964.43 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-15 14:33:23,915 epoch 10 - iter 1820/2606 - loss 0.01022403 - time (sec): 132.68 - samples/sec: 1946.26 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-15 14:33:42,085 epoch 10 - iter 2080/2606 - loss 0.00970005 - time (sec): 150.85 - samples/sec: 1945.45 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-15 14:34:00,746 epoch 10 - iter 2340/2606 - loss 0.00966883 - time (sec): 169.51 - samples/sec: 1948.61 - lr: 0.000000 - momentum: 0.000000 | |
| 2023-10-15 14:34:19,225 epoch 10 - iter 2600/2606 - loss 0.00993739 - time (sec): 187.99 - samples/sec: 1947.96 - lr: 0.000000 - momentum: 0.000000 | |
| 2023-10-15 14:34:19,749 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-15 14:34:19,749 EPOCH 10 done: loss 0.0099 - lr: 0.000000 | |
| 2023-10-15 14:34:28,121 DEV : loss 0.5089101195335388 - f1-score (micro avg) 0.375 | |
| 2023-10-15 14:34:28,509 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-15 14:34:28,510 Loading model from best epoch ... | |
| 2023-10-15 14:34:30,123 SequenceTagger predicts: Dictionary with 17 tags: O, S-LOC, B-LOC, E-LOC, I-LOC, S-PER, B-PER, E-PER, I-PER, S-ORG, B-ORG, E-ORG, I-ORG, S-HumanProd, B-HumanProd, E-HumanProd, I-HumanProd | |
| 2023-10-15 14:34:45,633 | |
| Results: | |
| - F-score (micro) 0.4364 | |
| - F-score (macro) 0.2809 | |
| - Accuracy 0.2836 | |
| By class: | |
| precision recall f1-score support | |
| LOC 0.5629 0.5198 0.5405 1214 | |
| PER 0.3648 0.4307 0.3950 808 | |
| ORG 0.2026 0.1756 0.1882 353 | |
| HumanProd 0.0000 0.0000 0.0000 15 | |
| micro avg 0.4372 0.4356 0.4364 2390 | |
| macro avg 0.2826 0.2815 0.2809 2390 | |
| weighted avg 0.4392 0.4356 0.4359 2390 | |
| 2023-10-15 14:34:45,634 ---------------------------------------------------------------------------------------------------- | |