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wav2vec2-base-timit-google-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: 0.4659
- Wer: 0.3080
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: 0.0001
- train_batch_size: 8
- 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: 1000
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 3.5787 | 0.87 | 500 | 1.7648 | 1.0305 |
| 0.8692 | 1.73 | 1000 | 0.5136 | 0.5103 |
| 0.4346 | 2.6 | 1500 | 0.4364 | 0.4515 |
| 0.31 | 3.46 | 2000 | 0.3889 | 0.4070 |
| 0.234 | 4.33 | 2500 | 0.4161 | 0.3863 |
| 0.2054 | 5.19 | 3000 | 0.3845 | 0.3722 |
| 0.165 | 6.06 | 3500 | 0.4035 | 0.3643 |
| 0.1436 | 6.92 | 4000 | 0.4090 | 0.3623 |
| 0.1381 | 7.79 | 4500 | 0.4007 | 0.3673 |
| 0.1175 | 8.65 | 5000 | 0.4588 | 0.3632 |
| 0.1052 | 9.52 | 5500 | 0.4441 | 0.3588 |
| 0.0988 | 10.38 | 6000 | 0.4133 | 0.3489 |
| 0.0877 | 11.25 | 6500 | 0.4758 | 0.3510 |
| 0.0856 | 12.11 | 7000 | 0.4454 | 0.3425 |
| 0.0731 | 12.98 | 7500 | 0.4252 | 0.3351 |
| 0.0712 | 13.84 | 8000 | 0.4163 | 0.3370 |
| 0.0711 | 14.71 | 8500 | 0.4166 | 0.3367 |
| 0.06 | 15.57 | 9000 | 0.4195 | 0.3347 |
| 0.0588 | 16.44 | 9500 | 0.4697 | 0.3367 |
| 0.0497 | 17.3 | 10000 | 0.4255 | 0.3314 |
| 0.0523 | 18.17 | 10500 | 0.4676 | 0.3307 |
| 0.0444 | 19.03 | 11000 | 0.4570 | 0.3244 |
| 0.0435 | 19.9 | 11500 | 0.4307 | 0.3243 |
| 0.0348 | 20.76 | 12000 | 0.4763 | 0.3245 |
| 0.036 | 21.63 | 12500 | 0.4635 | 0.3238 |
| 0.0347 | 22.49 | 13000 | 0.4602 | 0.3212 |
| 0.0333 | 23.36 | 13500 | 0.4472 | 0.3195 |
| 0.0311 | 24.22 | 14000 | 0.4449 | 0.3183 |
| 0.0294 | 25.09 | 14500 | 0.4631 | 0.3175 |
| 0.025 | 25.95 | 15000 | 0.4466 | 0.3164 |
| 0.023 | 26.82 | 15500 | 0.4581 | 0.3138 |
| 0.0216 | 27.68 | 16000 | 0.4665 | 0.3114 |
| 0.0198 | 28.55 | 16500 | 0.4590 | 0.3092 |
| 0.0181 | 29.41 | 17000 | 0.4659 | 0.3080 |
Framework versions
- Transformers 4.20.0.dev0
- Pytorch 1.11.0+cu113
- Datasets 1.18.3
- Tokenizers 0.12.1
