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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: google-bert/bert-base-uncased |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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- f1 |
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model-index: |
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- name: absa-bert |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# absa-bert |
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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. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.0596 |
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- Accuracy: 0.8281 |
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- F1: 0.7632 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-05 |
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- train_batch_size: 256 |
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- eval_batch_size: 256 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 100 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
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| 1.0575 | 1.0 | 12 | 0.9426 | 0.5933 | 0.2483 | |
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| 0.9027 | 2.0 | 24 | 0.8538 | 0.5952 | 0.2537 | |
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| 0.8016 | 3.0 | 36 | 0.7493 | 0.6876 | 0.4561 | |
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| 0.7066 | 4.0 | 48 | 0.6882 | 0.7246 | 0.5049 | |
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| 0.6343 | 5.0 | 60 | 0.6381 | 0.7394 | 0.5289 | |
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| 0.5703 | 6.0 | 72 | 0.6112 | 0.7542 | 0.6037 | |
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| 0.5229 | 7.0 | 84 | 0.6028 | 0.7634 | 0.6459 | |
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| 0.4864 | 8.0 | 96 | 0.6066 | 0.7634 | 0.6432 | |
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| 0.4479 | 9.0 | 108 | 0.6055 | 0.7689 | 0.6703 | |
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| 0.4154 | 10.0 | 120 | 0.5939 | 0.7708 | 0.6736 | |
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| 0.3815 | 11.0 | 132 | 0.6057 | 0.7708 | 0.6768 | |
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| 0.3525 | 12.0 | 144 | 0.6229 | 0.7689 | 0.6807 | |
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| 0.3229 | 13.0 | 156 | 0.6119 | 0.7745 | 0.6874 | |
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| 0.2962 | 14.0 | 168 | 0.6206 | 0.7874 | 0.7034 | |
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| 0.2718 | 15.0 | 180 | 0.6303 | 0.7726 | 0.6865 | |
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| 0.2448 | 16.0 | 192 | 0.6469 | 0.7745 | 0.6858 | |
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| 0.2241 | 17.0 | 204 | 0.6496 | 0.7745 | 0.6806 | |
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| 0.1985 | 18.0 | 216 | 0.6656 | 0.7763 | 0.6827 | |
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| 0.1784 | 19.0 | 228 | 0.6906 | 0.7726 | 0.6771 | |
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| 0.1693 | 20.0 | 240 | 0.6967 | 0.7856 | 0.7027 | |
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| 0.148 | 21.0 | 252 | 0.7059 | 0.7874 | 0.6945 | |
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| 0.1336 | 22.0 | 264 | 0.7480 | 0.7837 | 0.6823 | |
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| 0.1286 | 23.0 | 276 | 0.7424 | 0.7856 | 0.6896 | |
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| 0.1166 | 24.0 | 288 | 0.7293 | 0.7893 | 0.6970 | |
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| 0.1043 | 25.0 | 300 | 0.7177 | 0.7985 | 0.7151 | |
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| 0.0879 | 26.0 | 312 | 0.7184 | 0.8004 | 0.7237 | |
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| 0.0872 | 27.0 | 324 | 0.7407 | 0.7911 | 0.7121 | |
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| 0.0827 | 28.0 | 336 | 0.7513 | 0.7967 | 0.7193 | |
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| 0.0702 | 29.0 | 348 | 0.7797 | 0.8059 | 0.7261 | |
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| 0.0618 | 30.0 | 360 | 0.7911 | 0.8133 | 0.7378 | |
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| 0.0641 | 31.0 | 372 | 0.7861 | 0.8115 | 0.7369 | |
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| 0.051 | 32.0 | 384 | 0.8209 | 0.8078 | 0.7249 | |
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| 0.0473 | 33.0 | 396 | 0.7894 | 0.8133 | 0.7423 | |
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| 0.0463 | 34.0 | 408 | 0.8047 | 0.8152 | 0.7460 | |
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| 0.0447 | 35.0 | 420 | 0.8356 | 0.8133 | 0.7389 | |
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| 0.0408 | 36.0 | 432 | 0.8416 | 0.8078 | 0.7330 | |
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| 0.0393 | 37.0 | 444 | 0.8392 | 0.8133 | 0.7377 | |
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| 0.0356 | 38.0 | 456 | 0.8373 | 0.8207 | 0.7511 | |
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| 0.0387 | 39.0 | 468 | 0.8539 | 0.8096 | 0.7363 | |
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| 0.0347 | 40.0 | 480 | 0.8908 | 0.8078 | 0.7258 | |
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| 0.032 | 41.0 | 492 | 0.8500 | 0.8170 | 0.7474 | |
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| 0.0336 | 42.0 | 504 | 0.8515 | 0.8133 | 0.7423 | |
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| 0.0336 | 43.0 | 516 | 0.8515 | 0.8152 | 0.7407 | |
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| 0.0273 | 44.0 | 528 | 0.8832 | 0.8244 | 0.7497 | |
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| 0.0283 | 45.0 | 540 | 0.8701 | 0.8115 | 0.7398 | |
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| 0.0242 | 46.0 | 552 | 0.8904 | 0.8189 | 0.7487 | |
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| 0.027 | 47.0 | 564 | 0.8972 | 0.8244 | 0.7518 | |
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| 0.0275 | 48.0 | 576 | 0.8824 | 0.8189 | 0.7529 | |
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| 0.0197 | 49.0 | 588 | 0.9016 | 0.8152 | 0.7433 | |
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| 0.0205 | 50.0 | 600 | 0.9236 | 0.8152 | 0.7446 | |
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| 0.0235 | 51.0 | 612 | 0.9441 | 0.8189 | 0.7473 | |
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| 0.0215 | 52.0 | 624 | 0.9369 | 0.8207 | 0.7492 | |
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| 0.0195 | 53.0 | 636 | 0.9186 | 0.8244 | 0.7567 | |
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| 0.0155 | 54.0 | 648 | 0.9427 | 0.8244 | 0.7564 | |
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| 0.0184 | 55.0 | 660 | 0.9445 | 0.8226 | 0.7540 | |
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| 0.0159 | 56.0 | 672 | 0.9560 | 0.8189 | 0.7491 | |
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| 0.0172 | 57.0 | 684 | 0.9785 | 0.8152 | 0.7386 | |
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| 0.0151 | 58.0 | 696 | 0.9750 | 0.8152 | 0.7442 | |
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| 0.0159 | 59.0 | 708 | 0.9631 | 0.8207 | 0.7516 | |
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| 0.0126 | 60.0 | 720 | 1.0032 | 0.8189 | 0.7471 | |
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| 0.0153 | 61.0 | 732 | 0.9948 | 0.8170 | 0.7458 | |
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| 0.018 | 62.0 | 744 | 0.9880 | 0.8170 | 0.7494 | |
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| 0.0173 | 63.0 | 756 | 0.9989 | 0.8207 | 0.7523 | |
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| 0.0161 | 64.0 | 768 | 1.0125 | 0.8096 | 0.7313 | |
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| 0.0165 | 65.0 | 780 | 1.0105 | 0.8189 | 0.7474 | |
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| 0.0125 | 66.0 | 792 | 1.0118 | 0.8133 | 0.7374 | |
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| 0.0139 | 67.0 | 804 | 0.9968 | 0.8189 | 0.7514 | |
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| 0.0112 | 68.0 | 816 | 1.0152 | 0.8170 | 0.7442 | |
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| 0.0168 | 69.0 | 828 | 1.0176 | 0.8189 | 0.7463 | |
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| 0.0127 | 70.0 | 840 | 1.0108 | 0.8133 | 0.7404 | |
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| 0.0124 | 71.0 | 852 | 1.0187 | 0.8207 | 0.7487 | |
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| 0.0129 | 72.0 | 864 | 1.0138 | 0.8207 | 0.7531 | |
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| 0.0087 | 73.0 | 876 | 1.0301 | 0.8207 | 0.7481 | |
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| 0.0112 | 74.0 | 888 | 1.0131 | 0.8281 | 0.7629 | |
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| 0.0122 | 75.0 | 900 | 1.0176 | 0.8299 | 0.7658 | |
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| 0.0086 | 76.0 | 912 | 1.0301 | 0.8226 | 0.7543 | |
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| 0.0103 | 77.0 | 924 | 1.0421 | 0.8207 | 0.7527 | |
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| 0.0102 | 78.0 | 936 | 1.0410 | 0.8189 | 0.7480 | |
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| 0.0114 | 79.0 | 948 | 1.0451 | 0.8226 | 0.7539 | |
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| 0.0102 | 80.0 | 960 | 1.0286 | 0.8281 | 0.7632 | |
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| 0.0117 | 81.0 | 972 | 1.0311 | 0.8262 | 0.7603 | |
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| 0.0117 | 82.0 | 984 | 1.0386 | 0.8262 | 0.7589 | |
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| 0.0136 | 83.0 | 996 | 1.0320 | 0.8262 | 0.7603 | |
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| 0.01 | 84.0 | 1008 | 1.0304 | 0.8299 | 0.7679 | |
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| 0.0103 | 85.0 | 1020 | 1.0362 | 0.8262 | 0.7617 | |
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| 0.0105 | 86.0 | 1032 | 1.0440 | 0.8262 | 0.7617 | |
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| 0.0099 | 87.0 | 1044 | 1.0555 | 0.8244 | 0.7581 | |
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| 0.0117 | 88.0 | 1056 | 1.0615 | 0.8244 | 0.7571 | |
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| 0.0098 | 89.0 | 1068 | 1.0553 | 0.8262 | 0.7601 | |
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| 0.0105 | 90.0 | 1080 | 1.0586 | 0.8262 | 0.7603 | |
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| 0.0106 | 91.0 | 1092 | 1.0583 | 0.8262 | 0.7603 | |
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| 0.01 | 92.0 | 1104 | 1.0558 | 0.8262 | 0.7603 | |
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| 0.0105 | 93.0 | 1116 | 1.0589 | 0.8262 | 0.7603 | |
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| 0.011 | 94.0 | 1128 | 1.0609 | 0.8281 | 0.7632 | |
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| 0.0093 | 95.0 | 1140 | 1.0614 | 0.8281 | 0.7632 | |
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| 0.0096 | 96.0 | 1152 | 1.0615 | 0.8281 | 0.7632 | |
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| 0.0118 | 97.0 | 1164 | 1.0630 | 0.8281 | 0.7632 | |
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| 0.0089 | 98.0 | 1176 | 1.0618 | 0.8281 | 0.7632 | |
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| 0.0122 | 99.0 | 1188 | 1.0601 | 0.8281 | 0.7632 | |
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| 0.0101 | 100.0 | 1200 | 1.0596 | 0.8281 | 0.7632 | |
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### Framework versions |
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- Transformers 4.51.1 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.5.0 |
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- Tokenizers 0.21.0 |
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