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hubert-base-libri-demo-feature_extractor_frozen
This model is a fine-tuned version of facebook/hubert-base-ls960 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1217
- Wer: 0.3031
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: 0.00015
- train_batch_size: 64
- 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: 3000
- num_epochs: 25
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 4.446 | 1.12 | 500 | 3.5285 | 0.9999 |
| 2.8792 | 2.24 | 1000 | 3.2540 | 0.9999 |
| 2.8504 | 3.36 | 1500 | 3.0608 | 0.9999 |
| 1.2084 | 4.48 | 2000 | 0.3020 | 0.6763 |
| 0.3281 | 5.61 | 2500 | 0.1665 | 0.4887 |
| 0.2158 | 6.73 | 3000 | 0.1389 | 0.4071 |
| 0.179 | 7.85 | 3500 | 0.1294 | 0.3710 |
| 0.163 | 8.97 | 4000 | 0.1199 | 0.3592 |
| 0.1461 | 10.09 | 4500 | 0.1177 | 0.3485 |
| 0.1138 | 11.21 | 5000 | 0.1120 | 0.3374 |
| 0.1154 | 12.33 | 5500 | 0.1215 | 0.3307 |
| 0.0919 | 13.45 | 6000 | 0.1182 | 0.3279 |
| 0.0911 | 14.57 | 6500 | 0.1194 | 0.3286 |
| 0.0856 | 15.7 | 7000 | 0.1163 | 0.3185 |
| 0.0786 | 16.82 | 7500 | 0.1154 | 0.3193 |
| 0.0738 | 17.94 | 8000 | 0.1124 | 0.3122 |
| 0.0738 | 19.06 | 8500 | 0.1185 | 0.3105 |
| 0.0767 | 20.18 | 9000 | 0.1208 | 0.3061 |
| 0.0664 | 21.3 | 9500 | 0.1211 | 0.3050 |
| 0.0654 | 22.42 | 10000 | 0.1189 | 0.3039 |
| 0.0606 | 23.54 | 10500 | 0.1235 | 0.3041 |
| 0.0584 | 24.66 | 11000 | 0.1217 | 0.3031 |
Framework versions
- Transformers 4.30.0.dev0
- Pytorch 2.0.1
- Datasets 2.12.1.dev0
- Tokenizers 0.13.3
