wav2vec2-base-common-voice-40p-persian-colab
This model is a fine-tuned version of facebook/wav2vec2-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.1805
- Wer: 0.6024
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: 0.00018
- train_batch_size: 16
- 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: 2000
- num_epochs: 40
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 2.9643 | 1.05 | 200 | 3.0107 | 1.0 |
| 2.7552 | 2.11 | 400 | 2.7370 | 0.9997 |
| 1.9144 | 3.16 | 600 | 1.8266 | 0.9703 |
| 1.502 | 4.21 | 800 | 1.3981 | 0.8996 |
| 1.3155 | 5.26 | 1000 | 1.2148 | 0.8507 |
| 0.9471 | 6.32 | 1200 | 1.1698 | 0.7860 |
| 0.8391 | 7.37 | 1400 | 1.1106 | 0.7857 |
| 0.7986 | 8.42 | 1600 | 1.1858 | 0.7769 |
| 0.7692 | 9.47 | 1800 | 1.1227 | 0.7603 |
| 0.7871 | 10.53 | 2000 | 1.0626 | 0.7612 |
| 0.6795 | 11.58 | 2200 | 1.1249 | 0.7209 |
| 0.4842 | 12.63 | 2400 | 1.1626 | 0.7336 |
| 0.492 | 13.68 | 2600 | 1.0995 | 0.7212 |
| 0.5117 | 14.74 | 2800 | 1.1406 | 0.7105 |
| 0.5649 | 15.79 | 3000 | 1.0603 | 0.6819 |
| 0.3232 | 16.84 | 3200 | 1.1781 | 0.7070 |
| 0.4098 | 17.89 | 3400 | 1.1182 | 0.6764 |
| 0.3917 | 18.95 | 3600 | 1.1320 | 0.6750 |
| 0.3712 | 20.0 | 3800 | 1.1920 | 0.6724 |
| 0.3157 | 21.05 | 4000 | 1.1102 | 0.6786 |
| 0.2397 | 22.11 | 4200 | 1.1924 | 0.6519 |
| 0.2751 | 23.16 | 4400 | 1.1497 | 0.6468 |
| 0.2279 | 24.21 | 4600 | 1.2274 | 0.6400 |
| 0.393 | 25.26 | 4800 | 1.1741 | 0.6436 |
| 0.1748 | 26.32 | 5000 | 1.2038 | 0.6327 |
| 0.1727 | 27.37 | 5200 | 1.1639 | 0.6347 |
| 0.255 | 28.42 | 5400 | 1.1948 | 0.6367 |
| 0.2261 | 29.47 | 5600 | 1.1560 | 0.6362 |
| 0.2359 | 30.53 | 5800 | 1.1227 | 0.6269 |
| 0.1668 | 31.58 | 6000 | 1.1861 | 0.6295 |
| 0.1699 | 32.63 | 6200 | 1.2442 | 0.6314 |
| 0.14 | 33.68 | 6400 | 1.1340 | 0.6277 |
| 0.1919 | 34.74 | 6600 | 1.1691 | 0.6139 |
| 0.2527 | 35.79 | 6800 | 1.1511 | 0.6110 |
| 0.1219 | 36.84 | 7000 | 1.2062 | 0.6139 |
| 0.1389 | 37.89 | 7200 | 1.2142 | 0.6072 |
| 0.135 | 38.95 | 7400 | 1.1967 | 0.6040 |
| 0.1563 | 40.0 | 7600 | 1.1805 | 0.6024 |
Framework versions
- Transformers 4.11.3
- Pytorch 1.10.0+cu113
- Datasets 1.18.3
- Tokenizers 0.10.3