| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: t5-base |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: t5-base-squad-qag |
| results: [] |
| --- |
| |
| <!-- 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. --> |
|
|
| # t5-base-squad-qag |
|
|
| This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.1945 |
|
|
| ## 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: 8 |
| - eval_batch_size: 8 |
| - 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 | |
| |:-------------:|:-----:|:----:|:---------------:| |
| | No log | 1.0 | 7 | 12.2471 | |
| | No log | 2.0 | 14 | 7.2702 | |
| | No log | 3.0 | 21 | 5.6811 | |
| | No log | 4.0 | 28 | 4.6100 | |
| | No log | 5.0 | 35 | 0.6711 | |
| | No log | 6.0 | 42 | 0.4312 | |
| | No log | 7.0 | 49 | 0.4167 | |
| | No log | 8.0 | 56 | 0.4011 | |
| | No log | 9.0 | 63 | 0.3785 | |
| | No log | 10.0 | 70 | 0.3256 | |
| | No log | 11.0 | 77 | 0.2868 | |
| | No log | 12.0 | 84 | 0.2607 | |
| | No log | 13.0 | 91 | 0.2423 | |
| | No log | 14.0 | 98 | 0.2277 | |
| | No log | 15.0 | 105 | 0.2053 | |
| | No log | 16.0 | 112 | 0.1962 | |
| | No log | 17.0 | 119 | 0.1866 | |
| | No log | 18.0 | 126 | 0.1822 | |
| | No log | 19.0 | 133 | 0.1796 | |
| | No log | 20.0 | 140 | 0.1789 | |
| | No log | 21.0 | 147 | 0.1782 | |
| | No log | 22.0 | 154 | 0.1774 | |
| | No log | 23.0 | 161 | 0.1760 | |
| | No log | 24.0 | 168 | 0.1754 | |
| | No log | 25.0 | 175 | 0.1754 | |
| | No log | 26.0 | 182 | 0.1748 | |
| | No log | 27.0 | 189 | 0.1739 | |
| | No log | 28.0 | 196 | 0.1730 | |
| | No log | 29.0 | 203 | 0.1728 | |
| | No log | 30.0 | 210 | 0.1728 | |
| | No log | 31.0 | 217 | 0.1734 | |
| | No log | 32.0 | 224 | 0.1736 | |
| | No log | 33.0 | 231 | 0.1733 | |
| | No log | 34.0 | 238 | 0.1731 | |
| | No log | 35.0 | 245 | 0.1738 | |
| | No log | 36.0 | 252 | 0.1744 | |
| | No log | 37.0 | 259 | 0.1747 | |
| | No log | 38.0 | 266 | 0.1745 | |
| | No log | 39.0 | 273 | 0.1739 | |
| | No log | 40.0 | 280 | 0.1747 | |
| | No log | 41.0 | 287 | 0.1752 | |
| | No log | 42.0 | 294 | 0.1757 | |
| | No log | 43.0 | 301 | 0.1768 | |
| | No log | 44.0 | 308 | 0.1776 | |
| | No log | 45.0 | 315 | 0.1787 | |
| | No log | 46.0 | 322 | 0.1800 | |
| | No log | 47.0 | 329 | 0.1799 | |
| | No log | 48.0 | 336 | 0.1801 | |
| | No log | 49.0 | 343 | 0.1801 | |
| | No log | 50.0 | 350 | 0.1808 | |
| | No log | 51.0 | 357 | 0.1827 | |
| | No log | 52.0 | 364 | 0.1842 | |
| | No log | 53.0 | 371 | 0.1839 | |
| | No log | 54.0 | 378 | 0.1841 | |
| | No log | 55.0 | 385 | 0.1844 | |
| | No log | 56.0 | 392 | 0.1835 | |
| | No log | 57.0 | 399 | 0.1835 | |
| | No log | 58.0 | 406 | 0.1839 | |
| | No log | 59.0 | 413 | 0.1837 | |
| | No log | 60.0 | 420 | 0.1838 | |
| | No log | 61.0 | 427 | 0.1841 | |
| | No log | 62.0 | 434 | 0.1846 | |
| | No log | 63.0 | 441 | 0.1849 | |
| | No log | 64.0 | 448 | 0.1857 | |
| | No log | 65.0 | 455 | 0.1865 | |
| | No log | 66.0 | 462 | 0.1877 | |
| | No log | 67.0 | 469 | 0.1887 | |
| | No log | 68.0 | 476 | 0.1893 | |
| | No log | 69.0 | 483 | 0.1893 | |
| | No log | 70.0 | 490 | 0.1896 | |
| | No log | 71.0 | 497 | 0.1898 | |
| | 0.6248 | 72.0 | 504 | 0.1906 | |
| | 0.6248 | 73.0 | 511 | 0.1910 | |
| | 0.6248 | 74.0 | 518 | 0.1915 | |
| | 0.6248 | 75.0 | 525 | 0.1920 | |
| | 0.6248 | 76.0 | 532 | 0.1924 | |
| | 0.6248 | 77.0 | 539 | 0.1926 | |
| | 0.6248 | 78.0 | 546 | 0.1923 | |
| | 0.6248 | 79.0 | 553 | 0.1924 | |
| | 0.6248 | 80.0 | 560 | 0.1926 | |
| | 0.6248 | 81.0 | 567 | 0.1927 | |
| | 0.6248 | 82.0 | 574 | 0.1928 | |
| | 0.6248 | 83.0 | 581 | 0.1930 | |
| | 0.6248 | 84.0 | 588 | 0.1930 | |
| | 0.6248 | 85.0 | 595 | 0.1929 | |
| | 0.6248 | 86.0 | 602 | 0.1930 | |
| | 0.6248 | 87.0 | 609 | 0.1930 | |
| | 0.6248 | 88.0 | 616 | 0.1933 | |
| | 0.6248 | 89.0 | 623 | 0.1936 | |
| | 0.6248 | 90.0 | 630 | 0.1938 | |
| | 0.6248 | 91.0 | 637 | 0.1940 | |
| | 0.6248 | 92.0 | 644 | 0.1943 | |
| | 0.6248 | 93.0 | 651 | 0.1945 | |
| | 0.6248 | 94.0 | 658 | 0.1945 | |
| | 0.6248 | 95.0 | 665 | 0.1945 | |
| | 0.6248 | 96.0 | 672 | 0.1946 | |
| | 0.6248 | 97.0 | 679 | 0.1945 | |
| | 0.6248 | 98.0 | 686 | 0.1945 | |
| | 0.6248 | 99.0 | 693 | 0.1945 | |
| | 0.6248 | 100.0 | 700 | 0.1945 | |
|
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|
| ### Framework versions |
|
|
| - Transformers 4.48.3 |
| - Pytorch 2.5.1+cu124 |
| - Datasets 3.3.0 |
| - Tokenizers 0.21.0 |
|
|
