<!-- 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. -->
gen-qm-17-small
This model is a fine-tuned version of t5-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0339
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: 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: 60
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
1.2939 | 1.0 | 468 | 0.2461 |
0.3542 | 2.0 | 936 | 0.1119 |
0.21 | 3.0 | 1404 | 0.0772 |
0.1602 | 4.0 | 1872 | 0.0656 |
0.1325 | 5.0 | 2340 | 0.0579 |
0.116 | 6.0 | 2808 | 0.0527 |
0.1068 | 7.0 | 3276 | 0.0520 |
0.0986 | 8.0 | 3744 | 0.0497 |
0.0911 | 9.0 | 4212 | 0.0469 |
0.0849 | 10.0 | 4680 | 0.0449 |
0.0808 | 11.0 | 5148 | 0.0442 |
0.0783 | 12.0 | 5616 | 0.0433 |
0.0761 | 13.0 | 6084 | 0.0414 |
0.074 | 14.0 | 6552 | 0.0410 |
0.0715 | 15.0 | 7020 | 0.0408 |
0.068 | 16.0 | 7488 | 0.0402 |
0.0674 | 17.0 | 7956 | 0.0393 |
0.0661 | 18.0 | 8424 | 0.0399 |
0.0645 | 19.0 | 8892 | 0.0392 |
0.063 | 20.0 | 9360 | 0.0397 |
0.0619 | 21.0 | 9828 | 0.0382 |
0.0623 | 22.0 | 10296 | 0.0373 |
0.0609 | 23.0 | 10764 | 0.0372 |
0.0593 | 24.0 | 11232 | 0.0372 |
0.0584 | 25.0 | 11700 | 0.0369 |
0.0579 | 26.0 | 12168 | 0.0364 |
0.0572 | 27.0 | 12636 | 0.0365 |
0.0573 | 28.0 | 13104 | 0.0364 |
0.0556 | 29.0 | 13572 | 0.0363 |
0.0562 | 30.0 | 14040 | 0.0354 |
0.0544 | 31.0 | 14508 | 0.0358 |
0.0547 | 32.0 | 14976 | 0.0359 |
0.0529 | 33.0 | 15444 | 0.0353 |
0.0534 | 34.0 | 15912 | 0.0355 |
0.0524 | 35.0 | 16380 | 0.0353 |
0.052 | 36.0 | 16848 | 0.0354 |
0.0525 | 37.0 | 17316 | 0.0354 |
0.0533 | 38.0 | 17784 | 0.0351 |
0.0507 | 39.0 | 18252 | 0.0347 |
0.0504 | 40.0 | 18720 | 0.0347 |
0.0509 | 41.0 | 19188 | 0.0344 |
0.051 | 42.0 | 19656 | 0.0346 |
0.0507 | 43.0 | 20124 | 0.0342 |
0.0505 | 44.0 | 20592 | 0.0342 |
0.0497 | 45.0 | 21060 | 0.0344 |
0.0491 | 46.0 | 21528 | 0.0341 |
0.0489 | 47.0 | 21996 | 0.0340 |
0.0488 | 48.0 | 22464 | 0.0342 |
0.0481 | 49.0 | 22932 | 0.0338 |
0.0488 | 50.0 | 23400 | 0.0339 |
0.048 | 51.0 | 23868 | 0.0340 |
0.0481 | 52.0 | 24336 | 0.0341 |
0.0483 | 53.0 | 24804 | 0.0339 |
0.0492 | 54.0 | 25272 | 0.0339 |
0.0475 | 55.0 | 25740 | 0.0339 |
0.0477 | 56.0 | 26208 | 0.0339 |
0.0481 | 57.0 | 26676 | 0.0339 |
0.0478 | 58.0 | 27144 | 0.0338 |
0.0485 | 59.0 | 27612 | 0.0339 |
0.0479 | 60.0 | 28080 | 0.0339 |
Framework versions
- Transformers 4.27.3
- Pytorch 1.13.1
- Datasets 2.10.1
- Tokenizers 0.13.2