qa-persian-albert-fa-zwnj-base-v2
This model is a fine-tuned version of makhataei/qa-persian-albert-fa-zwnj-base-v2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 5.9720
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: 7.8125e-10
- train_batch_size: 14
- eval_batch_size: 14
- 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 |
|---|---|---|---|
| 6.0547 | 1.0 | 9 | 5.9759 |
| 6.1559 | 2.0 | 18 | 5.9758 |
| 6.1407 | 3.0 | 27 | 5.9757 |
| 6.2374 | 4.0 | 36 | 5.9756 |
| 6.1228 | 5.0 | 45 | 5.9755 |
| 6.0274 | 6.0 | 54 | 5.9754 |
| 6.175 | 7.0 | 63 | 5.9753 |
| 6.1089 | 8.0 | 72 | 5.9752 |
| 5.9715 | 9.0 | 81 | 5.9751 |
| 6.0709 | 10.0 | 90 | 5.9750 |
| 6.0287 | 11.0 | 99 | 5.9749 |
| 6.0229 | 12.0 | 108 | 5.9748 |
| 6.0991 | 13.0 | 117 | 5.9747 |
| 6.177 | 14.0 | 126 | 5.9746 |
| 6.0944 | 15.0 | 135 | 5.9745 |
| 6.1154 | 16.0 | 144 | 5.9744 |
| 6.1325 | 17.0 | 153 | 5.9743 |
| 6.032 | 18.0 | 162 | 5.9742 |
| 6.0753 | 19.0 | 171 | 5.9741 |
| 6.0302 | 20.0 | 180 | 5.9741 |
| 6.0986 | 21.0 | 189 | 5.9740 |
| 6.0651 | 22.0 | 198 | 5.9739 |
| 6.0975 | 23.0 | 207 | 5.9738 |
| 6.1147 | 24.0 | 216 | 5.9738 |
| 6.0799 | 25.0 | 225 | 5.9737 |
| 6.1036 | 26.0 | 234 | 5.9736 |
| 6.0992 | 27.0 | 243 | 5.9735 |
| 6.0736 | 28.0 | 252 | 5.9735 |
| 6.1135 | 29.0 | 261 | 5.9734 |
| 6.0838 | 30.0 | 270 | 5.9734 |
| 6.166 | 31.0 | 279 | 5.9733 |
| 6.1658 | 32.0 | 288 | 5.9732 |
| 6.0511 | 33.0 | 297 | 5.9732 |
| 6.0808 | 34.0 | 306 | 5.9731 |
| 6.3259 | 35.0 | 315 | 5.9731 |
| 6.5127 | 36.0 | 324 | 5.9730 |
| 6.1636 | 37.0 | 333 | 5.9730 |
| 6.0474 | 38.0 | 342 | 5.9729 |
| 6.0181 | 39.0 | 351 | 5.9729 |
| 6.2572 | 40.0 | 360 | 5.9729 |
| 6.1826 | 41.0 | 369 | 5.9728 |
| 6.0872 | 42.0 | 378 | 5.9728 |
| 6.5487 | 43.0 | 387 | 5.9728 |
| 6.0156 | 44.0 | 396 | 5.9727 |
| 6.0935 | 45.0 | 405 | 5.9727 |
| 6.1265 | 46.0 | 414 | 5.9727 |
| 6.0836 | 47.0 | 423 | 5.9726 |
| 6.3812 | 48.0 | 432 | 5.9726 |
| 6.1809 | 49.0 | 441 | 5.9726 |
| 6.189 | 50.0 | 450 | 5.9725 |
| 6.3619 | 51.0 | 459 | 5.9725 |
| 6.1027 | 52.0 | 468 | 5.9725 |
| 6.0734 | 53.0 | 477 | 5.9724 |
| 6.1045 | 54.0 | 486 | 5.9724 |
| 6.0697 | 55.0 | 495 | 5.9724 |
| 6.3692 | 56.0 | 504 | 5.9724 |
| 6.0849 | 57.0 | 513 | 5.9723 |
| 6.0133 | 58.0 | 522 | 5.9723 |
| 6.1366 | 59.0 | 531 | 5.9723 |
| 6.0863 | 60.0 | 540 | 5.9723 |
| 6.0564 | 61.0 | 549 | 5.9723 |
| 6.1513 | 62.0 | 558 | 5.9722 |
| 6.1085 | 63.0 | 567 | 5.9722 |
| 6.071 | 64.0 | 576 | 5.9722 |
| 6.0008 | 65.0 | 585 | 5.9722 |
| 6.1798 | 66.0 | 594 | 5.9722 |
| 6.14 | 67.0 | 603 | 5.9722 |
| 6.0828 | 68.0 | 612 | 5.9721 |
| 6.4297 | 69.0 | 621 | 5.9721 |
| 6.0881 | 70.0 | 630 | 5.9721 |
| 6.5834 | 71.0 | 639 | 5.9721 |
| 6.3729 | 72.0 | 648 | 5.9721 |
| 6.214 | 73.0 | 657 | 5.9721 |
| 6.1623 | 74.0 | 666 | 5.9721 |
| 6.7243 | 75.0 | 675 | 5.9721 |
| 6.0237 | 76.0 | 684 | 5.9721 |
| 6.099 | 77.0 | 693 | 5.9721 |
| 6.0 | 78.0 | 702 | 5.9721 |
| 6.0503 | 79.0 | 711 | 5.9721 |
| 6.3524 | 80.0 | 720 | 5.9721 |
| 6.4079 | 81.0 | 729 | 5.9720 |
| 6.0968 | 82.0 | 738 | 5.9720 |
| 5.9891 | 83.0 | 747 | 5.9720 |
| 6.2035 | 84.0 | 756 | 5.9720 |
| 6.0786 | 85.0 | 765 | 5.9720 |
| 6.0148 | 86.0 | 774 | 5.9720 |
| 6.2646 | 87.0 | 783 | 5.9720 |
| 6.1343 | 88.0 | 792 | 5.9720 |
| 6.0886 | 89.0 | 801 | 5.9720 |
| 6.0741 | 90.0 | 810 | 5.9720 |
| 6.0167 | 91.0 | 819 | 5.9720 |
| 6.0372 | 92.0 | 828 | 5.9720 |
| 6.1389 | 93.0 | 837 | 5.9720 |
| 6.2138 | 94.0 | 846 | 5.9720 |
| 6.0838 | 95.0 | 855 | 5.9720 |
| 6.0839 | 96.0 | 864 | 5.9720 |
| 6.3859 | 97.0 | 873 | 5.9720 |
| 6.1075 | 98.0 | 882 | 5.9720 |
| 6.0148 | 99.0 | 891 | 5.9720 |
| 6.1987 | 100.0 | 900 | 5.9720 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.0.1+cu117
- Datasets 2.15.0
- Tokenizers 0.15.0