--- library_name: transformers license: apache-2.0 base_model: google-bert/bert-base-uncased tags: - generated_from_trainer metrics: - accuracy - f1 model-index: - name: abte-bert results: [] --- # abte-bert This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.4438 - Accuracy: 0.9133 - F1: 0.9133 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 1e-05 - train_batch_size: 128 - eval_batch_size: 128 - seed: 42 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - num_epochs: 100 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| | 0.5077 | 1.0 | 24 | 0.3039 | 0.9166 | 0.9166 | | 0.2475 | 2.0 | 48 | 0.2232 | 0.9173 | 0.9173 | | 0.2026 | 3.0 | 72 | 0.1930 | 0.9208 | 0.9208 | | 0.1792 | 4.0 | 96 | 0.1744 | 0.9234 | 0.9234 | | 0.1646 | 5.0 | 120 | 0.1671 | 0.9231 | 0.9231 | | 0.155 | 6.0 | 144 | 0.1628 | 0.9229 | 0.9229 | | 0.1483 | 7.0 | 168 | 0.1604 | 0.9266 | 0.9266 | | 0.1426 | 8.0 | 192 | 0.1588 | 0.9266 | 0.9266 | | 0.1383 | 9.0 | 216 | 0.1607 | 0.9264 | 0.9264 | | 0.1347 | 10.0 | 240 | 0.1649 | 0.9241 | 0.9241 | | 0.1317 | 11.0 | 264 | 0.1651 | 0.9245 | 0.9245 | | 0.1277 | 12.0 | 288 | 0.1684 | 0.9242 | 0.9242 | | 0.1256 | 13.0 | 312 | 0.1735 | 0.9250 | 0.9250 | | 0.1239 | 14.0 | 336 | 0.1794 | 0.9280 | 0.9280 | | 0.1223 | 15.0 | 360 | 0.1837 | 0.9235 | 0.9235 | | 0.1208 | 16.0 | 384 | 0.1848 | 0.9228 | 0.9228 | | 0.119 | 17.0 | 408 | 0.1842 | 0.9265 | 0.9265 | | 0.1184 | 18.0 | 432 | 0.1895 | 0.9244 | 0.9244 | | 0.1174 | 19.0 | 456 | 0.1996 | 0.9201 | 0.9201 | | 0.117 | 20.0 | 480 | 0.1946 | 0.9220 | 0.9220 | | 0.1154 | 21.0 | 504 | 0.2086 | 0.9211 | 0.9211 | | 0.1141 | 22.0 | 528 | 0.2132 | 0.9212 | 0.9212 | | 0.1135 | 23.0 | 552 | 0.2282 | 0.9228 | 0.9228 | | 0.1123 | 24.0 | 576 | 0.2226 | 0.9214 | 0.9214 | | 0.1121 | 25.0 | 600 | 0.2274 | 0.9225 | 0.9225 | | 0.1109 | 26.0 | 624 | 0.2251 | 0.9224 | 0.9224 | | 0.111 | 27.0 | 648 | 0.2419 | 0.9186 | 0.9186 | | 0.1113 | 28.0 | 672 | 0.2555 | 0.9200 | 0.9200 | | 0.1104 | 29.0 | 696 | 0.2439 | 0.9206 | 0.9206 | | 0.1097 | 30.0 | 720 | 0.2613 | 0.9187 | 0.9187 | | 0.1092 | 31.0 | 744 | 0.2519 | 0.9195 | 0.9195 | | 0.1096 | 32.0 | 768 | 0.2539 | 0.9208 | 0.9208 | | 0.1092 | 33.0 | 792 | 0.2647 | 0.9231 | 0.9231 | | 0.1082 | 34.0 | 816 | 0.2677 | 0.9220 | 0.9220 | | 0.1082 | 35.0 | 840 | 0.2693 | 0.9222 | 0.9222 | | 0.1087 | 36.0 | 864 | 0.2818 | 0.9201 | 0.9201 | | 0.1082 | 37.0 | 888 | 0.2773 | 0.9206 | 0.9206 | | 0.1076 | 38.0 | 912 | 0.2882 | 0.9187 | 0.9187 | | 0.1067 | 39.0 | 936 | 0.2776 | 0.9199 | 0.9199 | | 0.1062 | 40.0 | 960 | 0.2850 | 0.9217 | 0.9217 | | 0.1065 | 41.0 | 984 | 0.3098 | 0.9188 | 0.9188 | | 0.1061 | 42.0 | 1008 | 0.3019 | 0.9191 | 0.9191 | | 0.1065 | 43.0 | 1032 | 0.2936 | 0.9175 | 0.9175 | | 0.1065 | 44.0 | 1056 | 0.3130 | 0.9197 | 0.9197 | | 0.1056 | 45.0 | 1080 | 0.3119 | 0.9170 | 0.9170 | | 0.1056 | 46.0 | 1104 | 0.3273 | 0.9171 | 0.9171 | | 0.1057 | 47.0 | 1128 | 0.3195 | 0.9200 | 0.9200 | | 0.1056 | 48.0 | 1152 | 0.3272 | 0.9171 | 0.9171 | | 0.1046 | 49.0 | 1176 | 0.3276 | 0.9187 | 0.9187 | | 0.1049 | 50.0 | 1200 | 0.3476 | 0.9152 | 0.9152 | | 0.1043 | 51.0 | 1224 | 0.3510 | 0.9171 | 0.9171 | | 0.1045 | 52.0 | 1248 | 0.3377 | 0.9177 | 0.9177 | | 0.1046 | 53.0 | 1272 | 0.3232 | 0.9200 | 0.9200 | | 0.1045 | 54.0 | 1296 | 0.3487 | 0.9147 | 0.9147 | | 0.104 | 55.0 | 1320 | 0.3422 | 0.9183 | 0.9183 | | 0.1041 | 56.0 | 1344 | 0.3609 | 0.9182 | 0.9182 | | 0.1036 | 57.0 | 1368 | 0.3602 | 0.9172 | 0.9172 | | 0.1041 | 58.0 | 1392 | 0.3627 | 0.9163 | 0.9163 | | 0.1038 | 59.0 | 1416 | 0.3672 | 0.9132 | 0.9132 | | 0.1044 | 60.0 | 1440 | 0.3597 | 0.9163 | 0.9163 | | 0.103 | 61.0 | 1464 | 0.3795 | 0.9163 | 0.9163 | | 0.104 | 62.0 | 1488 | 0.3635 | 0.9169 | 0.9169 | | 0.1034 | 63.0 | 1512 | 0.3777 | 0.9146 | 0.9146 | | 0.1033 | 64.0 | 1536 | 0.3772 | 0.9161 | 0.9161 | | 0.1037 | 65.0 | 1560 | 0.3925 | 0.9140 | 0.9140 | | 0.103 | 66.0 | 1584 | 0.3923 | 0.9157 | 0.9157 | | 0.1027 | 67.0 | 1608 | 0.3711 | 0.9178 | 0.9178 | | 0.103 | 68.0 | 1632 | 0.4019 | 0.9156 | 0.9156 | | 0.1032 | 69.0 | 1656 | 0.3967 | 0.9134 | 0.9134 | | 0.1026 | 70.0 | 1680 | 0.4072 | 0.9141 | 0.9141 | | 0.1029 | 71.0 | 1704 | 0.4065 | 0.9136 | 0.9136 | | 0.1023 | 72.0 | 1728 | 0.3933 | 0.9171 | 0.9171 | | 0.1024 | 73.0 | 1752 | 0.4131 | 0.9109 | 0.9109 | | 0.1029 | 74.0 | 1776 | 0.4001 | 0.9150 | 0.9150 | | 0.1018 | 75.0 | 1800 | 0.4171 | 0.9132 | 0.9132 | | 0.1022 | 76.0 | 1824 | 0.4151 | 0.9144 | 0.9144 | | 0.1025 | 77.0 | 1848 | 0.4194 | 0.9149 | 0.9149 | | 0.1022 | 78.0 | 1872 | 0.4238 | 0.9132 | 0.9132 | | 0.1021 | 79.0 | 1896 | 0.4328 | 0.9133 | 0.9133 | | 0.102 | 80.0 | 1920 | 0.4241 | 0.9113 | 0.9113 | | 0.1023 | 81.0 | 1944 | 0.4214 | 0.9146 | 0.9146 | | 0.1023 | 82.0 | 1968 | 0.4324 | 0.9136 | 0.9136 | | 0.1021 | 83.0 | 1992 | 0.4251 | 0.9153 | 0.9153 | | 0.1017 | 84.0 | 2016 | 0.4366 | 0.9138 | 0.9138 | | 0.1017 | 85.0 | 2040 | 0.4405 | 0.9135 | 0.9135 | | 0.1021 | 86.0 | 2064 | 0.4337 | 0.9156 | 0.9156 | | 0.1019 | 87.0 | 2088 | 0.4343 | 0.9130 | 0.9130 | | 0.1021 | 88.0 | 2112 | 0.4360 | 0.9145 | 0.9145 | | 0.1018 | 89.0 | 2136 | 0.4425 | 0.9143 | 0.9143 | | 0.1014 | 90.0 | 2160 | 0.4438 | 0.9131 | 0.9131 | | 0.1017 | 91.0 | 2184 | 0.4409 | 0.9128 | 0.9128 | | 0.1018 | 92.0 | 2208 | 0.4402 | 0.9136 | 0.9136 | | 0.1015 | 93.0 | 2232 | 0.4432 | 0.9131 | 0.9131 | | 0.1016 | 94.0 | 2256 | 0.4453 | 0.9126 | 0.9126 | | 0.1017 | 95.0 | 2280 | 0.4495 | 0.9139 | 0.9139 | | 0.1016 | 96.0 | 2304 | 0.4465 | 0.9135 | 0.9135 | | 0.1019 | 97.0 | 2328 | 0.4433 | 0.9134 | 0.9134 | | 0.1016 | 98.0 | 2352 | 0.4439 | 0.9128 | 0.9128 | | 0.102 | 99.0 | 2376 | 0.4432 | 0.9134 | 0.9134 | | 0.1014 | 100.0 | 2400 | 0.4438 | 0.9133 | 0.9133 | ### Framework versions - Transformers 4.51.3 - Pytorch 2.6.0+cu124 - Datasets 3.5.1 - Tokenizers 0.21.1