--- tags: - generated_from_trainer model-index: - name: GQA_BERT_legal_SQuAD_complete_augmented_100 results: [] --- # GQA_BERT_legal_SQuAD_complete_augmented_100 This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.0964 ## 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: 2e-05 - train_batch_size: 160 - eval_batch_size: 40 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 100 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | No log | 1.0 | 3 | 5.1190 | | No log | 2.0 | 6 | 4.5892 | | No log | 3.0 | 9 | 3.9684 | | No log | 4.0 | 12 | 3.6427 | | No log | 5.0 | 15 | 3.2081 | | No log | 6.0 | 18 | 2.8413 | | No log | 7.0 | 21 | 2.5487 | | No log | 8.0 | 24 | 2.2830 | | No log | 9.0 | 27 | 2.0807 | | No log | 10.0 | 30 | 1.8644 | | No log | 11.0 | 33 | 1.7166 | | No log | 12.0 | 36 | 1.5672 | | No log | 13.0 | 39 | 1.3949 | | No log | 14.0 | 42 | 1.3109 | | No log | 15.0 | 45 | 1.2622 | | No log | 16.0 | 48 | 1.1875 | | No log | 17.0 | 51 | 1.1579 | | No log | 18.0 | 54 | 1.1329 | | No log | 19.0 | 57 | 1.1090 | | No log | 20.0 | 60 | 1.0811 | | No log | 21.0 | 63 | 1.0542 | | No log | 22.0 | 66 | 1.0481 | | No log | 23.0 | 69 | 1.0355 | | No log | 24.0 | 72 | 1.0304 | | No log | 25.0 | 75 | 1.0276 | | No log | 26.0 | 78 | 1.0277 | | No log | 27.0 | 81 | 1.0329 | | No log | 28.0 | 84 | 1.0356 | | No log | 29.0 | 87 | 1.0410 | | No log | 30.0 | 90 | 1.0267 | | No log | 31.0 | 93 | 1.0280 | | No log | 32.0 | 96 | 1.0453 | | No log | 33.0 | 99 | 1.0520 | | No log | 34.0 | 102 | 1.0430 | | No log | 35.0 | 105 | 1.0393 | | No log | 36.0 | 108 | 1.0370 | | No log | 37.0 | 111 | 1.0284 | | No log | 38.0 | 114 | 1.0313 | | No log | 39.0 | 117 | 1.0376 | | No log | 40.0 | 120 | 1.0312 | | No log | 41.0 | 123 | 1.0218 | | No log | 42.0 | 126 | 1.0348 | | No log | 43.0 | 129 | 1.0426 | | No log | 44.0 | 132 | 1.0411 | | No log | 45.0 | 135 | 1.0463 | | No log | 46.0 | 138 | 1.0661 | | No log | 47.0 | 141 | 1.0733 | | No log | 48.0 | 144 | 1.0609 | | No log | 49.0 | 147 | 1.0578 | | No log | 50.0 | 150 | 1.0639 | | No log | 51.0 | 153 | 1.0490 | | No log | 52.0 | 156 | 1.0507 | | No log | 53.0 | 159 | 1.0460 | | No log | 54.0 | 162 | 1.0534 | | No log | 55.0 | 165 | 1.0530 | | No log | 56.0 | 168 | 1.0521 | | No log | 57.0 | 171 | 1.0470 | | No log | 58.0 | 174 | 1.0462 | | No log | 59.0 | 177 | 1.0547 | | No log | 60.0 | 180 | 1.0628 | | No log | 61.0 | 183 | 1.0550 | | No log | 62.0 | 186 | 1.0474 | | No log | 63.0 | 189 | 1.0536 | | No log | 64.0 | 192 | 1.0711 | | No log | 65.0 | 195 | 1.0832 | | No log | 66.0 | 198 | 1.0855 | | No log | 67.0 | 201 | 1.0901 | | No log | 68.0 | 204 | 1.0912 | | No log | 69.0 | 207 | 1.0888 | | No log | 70.0 | 210 | 1.0882 | | No log | 71.0 | 213 | 1.0985 | | No log | 72.0 | 216 | 1.1056 | | No log | 73.0 | 219 | 1.0876 | | No log | 74.0 | 222 | 1.0781 | | No log | 75.0 | 225 | 1.0894 | | No log | 76.0 | 228 | 1.0906 | | No log | 77.0 | 231 | 1.0848 | | No log | 78.0 | 234 | 1.0851 | | No log | 79.0 | 237 | 1.0949 | | No log | 80.0 | 240 | 1.0982 | | No log | 81.0 | 243 | 1.0932 | | No log | 82.0 | 246 | 1.0825 | | No log | 83.0 | 249 | 1.0791 | | No log | 84.0 | 252 | 1.0821 | | No log | 85.0 | 255 | 1.0819 | | No log | 86.0 | 258 | 1.0808 | | No log | 87.0 | 261 | 1.0794 | | No log | 88.0 | 264 | 1.0815 | | No log | 89.0 | 267 | 1.0859 | | No log | 90.0 | 270 | 1.0883 | | No log | 91.0 | 273 | 1.0890 | | No log | 92.0 | 276 | 1.0935 | | No log | 93.0 | 279 | 1.0982 | | No log | 94.0 | 282 | 1.1007 | | No log | 95.0 | 285 | 1.0994 | | No log | 96.0 | 288 | 1.0997 | | No log | 97.0 | 291 | 1.0998 | | No log | 98.0 | 294 | 1.0978 | | No log | 99.0 | 297 | 1.0970 | | No log | 100.0 | 300 | 1.0964 | ### Framework versions - Transformers 4.36.2 - Pytorch 2.1.2+cu121 - Datasets 2.14.7 - Tokenizers 0.15.0