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whisper-medium-ar-no_diacritics
This model is a fine-tuned version of openai/whisper-medium on the audiofolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.1762
- Wer: 7.4970
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: 1e-05
- train_batch_size: 24
- eval_batch_size: 24
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 8000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1114 | 1.01 | 400 | 0.1300 | 9.9764 |
| 0.0682 | 2.02 | 800 | 0.1157 | 8.9138 |
| 0.0302 | 3.03 | 1200 | 0.1274 | 8.2645 |
| 0.0151 | 4.04 | 1600 | 0.1277 | 7.7922 |
| 0.0104 | 5.05 | 2000 | 0.1304 | 7.7922 |
| 0.0069 | 6.06 | 2400 | 0.1476 | 8.4416 |
| 0.0033 | 7.07 | 2800 | 0.1307 | 7.7332 |
| 0.0026 | 8.08 | 3200 | 0.1425 | 8.3235 |
| 0.001 | 9.09 | 3600 | 0.1530 | 8.2054 |
| 0.0006 | 10.1 | 4000 | 0.1586 | 7.9693 |
| 0.0008 | 11.11 | 4400 | 0.1601 | 7.6151 |
| 0.001 | 12.12 | 4800 | 0.1647 | 8.0874 |
| 0.001 | 13.13 | 5200 | 0.1650 | 7.7332 |
| 0.0001 | 14.14 | 5600 | 0.1671 | 7.4380 |
| 0.0001 | 15.15 | 6000 | 0.1694 | 7.2609 |
| 0.0001 | 16.16 | 6400 | 0.1726 | 7.4970 |
| 0.0002 | 17.17 | 6800 | 0.1744 | 7.4380 |
| 0.0001 | 18.18 | 7200 | 0.1752 | 7.4970 |
| 0.0 | 19.19 | 7600 | 0.1758 | 7.4970 |
| 0.0 | 20.2 | 8000 | 0.1762 | 7.4970 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.12.1
- Datasets 2.8.0
- Tokenizers 0.13.2
