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hubert-base-libri-demo-feature_extractor_not_frozen_v2
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: 0.1152
- Wer: 0.1118
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 |
|---|---|---|---|---|
| 4.3761 | 1.12 | 500 | 3.4742 | 1.0 |
| 2.882 | 2.24 | 1000 | 3.6180 | 1.0 |
| 2.8637 | 3.36 | 1500 | 3.0941 | 1.0 |
| 1.2198 | 4.48 | 2000 | 0.3003 | 0.3313 |
| 0.3296 | 5.61 | 2500 | 0.1670 | 0.2085 |
| 0.2195 | 6.73 | 3000 | 0.1393 | 0.1615 |
| 0.1832 | 7.85 | 3500 | 0.1284 | 0.1445 |
| 0.166 | 8.97 | 4000 | 0.1227 | 0.1362 |
| 0.1491 | 10.09 | 4500 | 0.1201 | 0.1305 |
| 0.1157 | 11.21 | 5000 | 0.1141 | 0.1262 |
| 0.1175 | 12.33 | 5500 | 0.1311 | 0.1250 |
| 0.0939 | 13.45 | 6000 | 0.1227 | 0.1205 |
| 0.0919 | 14.57 | 6500 | 0.1234 | 0.1205 |
| 0.0871 | 15.7 | 7000 | 0.1141 | 0.1187 |
| 0.0792 | 16.82 | 7500 | 0.1154 | 0.1171 |
| 0.0746 | 17.94 | 8000 | 0.1118 | 0.1157 |
| 0.074 | 19.06 | 8500 | 0.1159 | 0.1147 |
| 0.077 | 20.18 | 9000 | 0.1172 | 0.1137 |
| 0.0662 | 21.3 | 9500 | 0.1158 | 0.1126 |
| 0.0652 | 22.42 | 10000 | 0.1146 | 0.1117 |
| 0.06 | 23.54 | 10500 | 0.1159 | 0.1117 |
| 0.0576 | 24.66 | 11000 | 0.1152 | 0.1118 |
Framework versions
- Transformers 4.30.0.dev0
- Pytorch 2.0.1
- Datasets 2.12.1.dev0
- Tokenizers 0.13.3
