<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->
distilbert-base-cased-distilled-squad-finetuned-lr1e-08-epochs100
This model is a fine-tuned version of distilbert-base-cased-distilled-squad on the None dataset. It achieves the following results on the evaluation set:
- Loss: 4.7336
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-08
- train_batch_size: 32
- eval_batch_size: 32
- 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 | 4 | 4.7927 |
| No log | 2.0 | 8 | 4.7914 |
| No log | 3.0 | 12 | 4.7901 |
| No log | 4.0 | 16 | 4.7888 |
| No log | 5.0 | 20 | 4.7876 |
| No log | 6.0 | 24 | 4.7864 |
| No log | 7.0 | 28 | 4.7851 |
| No log | 8.0 | 32 | 4.7839 |
| No log | 9.0 | 36 | 4.7827 |
| No log | 10.0 | 40 | 4.7815 |
| No log | 11.0 | 44 | 4.7804 |
| No log | 12.0 | 48 | 4.7792 |
| No log | 13.0 | 52 | 4.7781 |
| No log | 14.0 | 56 | 4.7769 |
| No log | 15.0 | 60 | 4.7758 |
| No log | 16.0 | 64 | 4.7747 |
| No log | 17.0 | 68 | 4.7735 |
| No log | 18.0 | 72 | 4.7724 |
| No log | 19.0 | 76 | 4.7713 |
| No log | 20.0 | 80 | 4.7703 |
| No log | 21.0 | 84 | 4.7692 |
| No log | 22.0 | 88 | 4.7682 |
| No log | 23.0 | 92 | 4.7672 |
| No log | 24.0 | 96 | 4.7662 |
| No log | 25.0 | 100 | 4.7652 |
| No log | 26.0 | 104 | 4.7642 |
| No log | 27.0 | 108 | 4.7633 |
| No log | 28.0 | 112 | 4.7623 |
| No log | 29.0 | 116 | 4.7614 |
| No log | 30.0 | 120 | 4.7604 |
| No log | 31.0 | 124 | 4.7595 |
| No log | 32.0 | 128 | 4.7586 |
| No log | 33.0 | 132 | 4.7577 |
| No log | 34.0 | 136 | 4.7569 |
| No log | 35.0 | 140 | 4.7560 |
| No log | 36.0 | 144 | 4.7552 |
| No log | 37.0 | 148 | 4.7544 |
| No log | 38.0 | 152 | 4.7535 |
| No log | 39.0 | 156 | 4.7528 |
| No log | 40.0 | 160 | 4.7520 |
| No log | 41.0 | 164 | 4.7513 |
| No log | 42.0 | 168 | 4.7506 |
| No log | 43.0 | 172 | 4.7499 |
| No log | 44.0 | 176 | 4.7492 |
| No log | 45.0 | 180 | 4.7485 |
| No log | 46.0 | 184 | 4.7478 |
| No log | 47.0 | 188 | 4.7472 |
| No log | 48.0 | 192 | 4.7466 |
| No log | 49.0 | 196 | 4.7460 |
| No log | 50.0 | 200 | 4.7454 |
| No log | 51.0 | 204 | 4.7448 |
| No log | 52.0 | 208 | 4.7442 |
| No log | 53.0 | 212 | 4.7437 |
| No log | 54.0 | 216 | 4.7431 |
| No log | 55.0 | 220 | 4.7426 |
| No log | 56.0 | 224 | 4.7421 |
| No log | 57.0 | 228 | 4.7416 |
| No log | 58.0 | 232 | 4.7411 |
| No log | 59.0 | 236 | 4.7406 |
| No log | 60.0 | 240 | 4.7401 |
| No log | 61.0 | 244 | 4.7397 |
| No log | 62.0 | 248 | 4.7393 |
| No log | 63.0 | 252 | 4.7388 |
| No log | 64.0 | 256 | 4.7385 |
| No log | 65.0 | 260 | 4.7381 |
| No log | 66.0 | 264 | 4.7377 |
| No log | 67.0 | 268 | 4.7374 |
| No log | 68.0 | 272 | 4.7370 |
| No log | 69.0 | 276 | 4.7367 |
| No log | 70.0 | 280 | 4.7364 |
| No log | 71.0 | 284 | 4.7361 |
| No log | 72.0 | 288 | 4.7359 |
| No log | 73.0 | 292 | 4.7356 |
| No log | 74.0 | 296 | 4.7354 |
| No log | 75.0 | 300 | 4.7351 |
| No log | 76.0 | 304 | 4.7349 |
| No log | 77.0 | 308 | 4.7348 |
| No log | 78.0 | 312 | 4.7346 |
| No log | 79.0 | 316 | 4.7345 |
| No log | 80.0 | 320 | 4.7343 |
| No log | 81.0 | 324 | 4.7342 |
| No log | 82.0 | 328 | 4.7341 |
| No log | 83.0 | 332 | 4.7340 |
| No log | 84.0 | 336 | 4.7339 |
| No log | 85.0 | 340 | 4.7338 |
| No log | 86.0 | 344 | 4.7337 |
| No log | 87.0 | 348 | 4.7337 |
| No log | 88.0 | 352 | 4.7337 |
| No log | 89.0 | 356 | 4.7336 |
| No log | 90.0 | 360 | 4.7336 |
| No log | 91.0 | 364 | 4.7336 |
| No log | 92.0 | 368 | 4.7336 |
| No log | 93.0 | 372 | 4.7336 |
| No log | 94.0 | 376 | 4.7336 |
| No log | 95.0 | 380 | 4.7336 |
| No log | 96.0 | 384 | 4.7336 |
| No log | 97.0 | 388 | 4.7336 |
| No log | 98.0 | 392 | 4.7336 |
| No log | 99.0 | 396 | 4.7336 |
| No log | 100.0 | 400 | 4.7336 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
