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hubert-base-libri-demo-feature_extractor_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: 0.1202
- Wer: 0.1115
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 |
|---|---|---|---|---|
| 4.401 | 1.12 | 500 | 3.5086 | 1.0 |
| 2.8748 | 2.24 | 1000 | 3.3953 | 1.0 |
| 2.2716 | 3.36 | 1500 | 0.7177 | 0.6110 |
| 0.5536 | 4.48 | 2000 | 0.2387 | 0.2692 |
| 0.2897 | 5.61 | 2500 | 0.1593 | 0.1946 |
| 0.2077 | 6.73 | 3000 | 0.1401 | 0.1558 |
| 0.1778 | 7.85 | 3500 | 0.1225 | 0.1423 |
| 0.1639 | 8.97 | 4000 | 0.1156 | 0.1342 |
| 0.1478 | 10.09 | 4500 | 0.1186 | 0.1290 |
| 0.1146 | 11.21 | 5000 | 0.1131 | 0.1244 |
| 0.1172 | 12.33 | 5500 | 0.1189 | 0.1235 |
| 0.0925 | 13.45 | 6000 | 0.1175 | 0.1214 |
| 0.092 | 14.57 | 6500 | 0.1224 | 0.1194 |
| 0.0865 | 15.7 | 7000 | 0.1160 | 0.1196 |
| 0.0786 | 16.82 | 7500 | 0.1151 | 0.1152 |
| 0.0743 | 17.94 | 8000 | 0.1124 | 0.1153 |
| 0.0739 | 19.06 | 8500 | 0.1214 | 0.1146 |
| 0.0774 | 20.18 | 9000 | 0.1219 | 0.1143 |
| 0.0667 | 21.3 | 9500 | 0.1188 | 0.1129 |
| 0.0661 | 22.42 | 10000 | 0.1176 | 0.1123 |
| 0.0606 | 23.54 | 10500 | 0.1201 | 0.1118 |
| 0.0584 | 24.66 | 11000 | 0.1202 | 0.1115 |
Framework versions
- Transformers 4.30.0.dev0
- Pytorch 2.0.1
- Datasets 2.12.1.dev0
- Tokenizers 0.13.3
