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
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