hubert-base-libri-demo-feature_extractor_not_frozen_v4_25epochs_weight_decay
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: 0.1189
- Wer: 0.1105
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 |
---|---|---|---|---|
4.3661 | 1.12 | 500 | 3.4415 | 0.9837 |
2.8763 | 2.24 | 1000 | 3.1292 | 0.9837 |
1.6666 | 3.36 | 1500 | 0.5027 | 0.4804 |
0.4759 | 4.48 | 2000 | 0.2187 | 0.2536 |
0.2774 | 5.61 | 2500 | 0.1555 | 0.1898 |
0.2026 | 6.73 | 3000 | 0.1297 | 0.1543 |
0.1745 | 7.85 | 3500 | 0.1201 | 0.1419 |
0.1596 | 8.97 | 4000 | 0.1220 | 0.1339 |
0.1449 | 10.09 | 4500 | 0.1156 | 0.1280 |
0.1134 | 11.21 | 5000 | 0.1131 | 0.1244 |
0.1143 | 12.33 | 5500 | 0.1189 | 0.1226 |
0.0915 | 13.45 | 6000 | 0.1138 | 0.1196 |
0.0904 | 14.57 | 6500 | 0.1125 | 0.1195 |
0.0853 | 15.7 | 7000 | 0.1125 | 0.1168 |
0.0775 | 16.82 | 7500 | 0.1103 | 0.1155 |
0.0732 | 17.94 | 8000 | 0.1115 | 0.1138 |
0.0728 | 19.06 | 8500 | 0.1196 | 0.1142 |
0.0755 | 20.18 | 9000 | 0.1170 | 0.1122 |
0.0647 | 21.3 | 9500 | 0.1167 | 0.1117 |
0.064 | 22.42 | 10000 | 0.1177 | 0.1109 |
0.0591 | 23.54 | 10500 | 0.1182 | 0.1110 |
0.0566 | 24.66 | 11000 | 0.1189 | 0.1105 |
Framework versions
- Transformers 4.30.0.dev0
- Pytorch 2.0.1
- Datasets 2.12.1.dev0
- Tokenizers 0.13.3
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