wav2vec2-large-robust-paper
This model is a fine-tuned version of facebook/wav2vec2-large-robust on the HTS98/ORIGINAL_VER1.2 - NA dataset. It achieves the following results on the evaluation set:
- Loss: 0.8696
- Wer: 0.4572
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: 5e-05
- train_batch_size: 10
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 420
- num_epochs: 50.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| No log | 1.0 | 335 | 3.9163 | 1.0 |
| 7.1369 | 2.0 | 670 | 3.3422 | 1.0 |
| 3.3448 | 3.0 | 1005 | 3.3355 | 1.0 |
| 3.3448 | 4.0 | 1340 | 3.3263 | 1.0 |
| 3.3277 | 5.0 | 1675 | 2.8928 | 1.0079 |
| 2.6655 | 6.0 | 2010 | 1.7822 | 0.8788 |
| 2.6655 | 7.0 | 2345 | 1.3193 | 0.7055 |
| 1.4617 | 8.0 | 2680 | 1.1408 | 0.6070 |
| 1.0805 | 9.0 | 3015 | 1.0108 | 0.5422 |
| 1.0805 | 10.0 | 3350 | 0.9517 | 0.5154 |
| 0.8759 | 11.0 | 3685 | 0.9082 | 0.4902 |
| 0.7462 | 12.0 | 4020 | 0.8758 | 0.4706 |
| 0.7462 | 13.0 | 4355 | 0.8696 | 0.4572 |
| 0.6429 | 14.0 | 4690 | 0.8731 | 0.4535 |
| 0.5672 | 15.0 | 5025 | 0.8749 | 0.4508 |
| 0.5672 | 16.0 | 5360 | 0.8753 | 0.4512 |
| 0.4959 | 17.0 | 5695 | 0.9039 | 0.4487 |
| 0.4456 | 18.0 | 6030 | 0.9161 | 0.4433 |
| 0.4456 | 19.0 | 6365 | 0.9506 | 0.4430 |
| 0.392 | 20.0 | 6700 | 0.9412 | 0.4439 |
| 0.3594 | 21.0 | 7035 | 0.9884 | 0.4416 |
| 0.3594 | 22.0 | 7370 | 1.0222 | 0.4510 |
| 0.3175 | 23.0 | 7705 | 1.0345 | 0.4439 |
| 0.2947 | 24.0 | 8040 | 1.0849 | 0.4465 |
| 0.2947 | 25.0 | 8375 | 1.0879 | 0.4472 |
| 0.2674 | 26.0 | 8710 | 1.1071 | 0.4512 |
| 0.2521 | 27.0 | 9045 | 1.1147 | 0.4494 |
| 0.2521 | 28.0 | 9380 | 1.1426 | 0.4525 |
| 0.2321 | 29.0 | 9715 | 1.1592 | 0.4440 |
| 0.2235 | 30.0 | 10050 | 1.1782 | 0.4450 |
| 0.2235 | 31.0 | 10385 | 1.2050 | 0.4437 |
| 0.2071 | 32.0 | 10720 | 1.2224 | 0.4400 |
| 0.1951 | 33.0 | 11055 | 1.2270 | 0.4471 |
| 0.1951 | 34.0 | 11390 | 1.2466 | 0.4483 |
| 0.1892 | 35.0 | 11725 | 1.2325 | 0.4429 |
| 0.1809 | 36.0 | 12060 | 1.2755 | 0.4427 |
| 0.1809 | 37.0 | 12395 | 1.2675 | 0.4422 |
| 0.1746 | 38.0 | 12730 | 1.3022 | 0.4418 |
| 0.1656 | 39.0 | 13065 | 1.3179 | 0.4408 |
| 0.1656 | 40.0 | 13400 | 1.2934 | 0.4425 |
| 0.1614 | 41.0 | 13735 | 1.3304 | 0.4426 |
| 0.1564 | 42.0 | 14070 | 1.3148 | 0.4420 |
| 0.1564 | 43.0 | 14405 | 1.3267 | 0.4433 |
| 0.1546 | 44.0 | 14740 | 1.3331 | 0.4413 |
| 0.1515 | 45.0 | 15075 | 1.3445 | 0.4388 |
| 0.1515 | 46.0 | 15410 | 1.3530 | 0.4372 |
| 0.147 | 47.0 | 15745 | 1.3443 | 0.4385 |
| 0.1447 | 48.0 | 16080 | 1.3503 | 0.4369 |
| 0.1447 | 49.0 | 16415 | 1.3590 | 0.4393 |
| 0.1437 | 50.0 | 16750 | 1.3668 | 0.4372 |
Framework versions
- Transformers 4.31.0.dev0
- Pytorch 2.0.0+cu117
- Datasets 2.7.0
- Tokenizers 0.13.2