whisper-v3-dyu4
This model is a fine-tuned version of openai/whisper-large-v3 on the abdouaziiz/wolof_lam_asr dataset. It achieves the following results on the evaluation set:
- Loss: 0.4723
- Wer: 0.3675
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: 2e-05
- train_batch_size: 12
- eval_batch_size: 12
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 32000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.8017 | 0.3106 | 500 | 0.7470 | 0.4962 |
| 0.6325 | 0.6211 | 1000 | 0.6371 | 0.3837 |
| 0.5929 | 0.9317 | 1500 | 0.5565 | 0.3274 |
| 0.3732 | 1.2422 | 2000 | 0.5384 | 0.4248 |
| 0.3639 | 1.5528 | 2500 | 0.5200 | 0.3033 |
| 0.3754 | 1.8634 | 3000 | 0.4936 | 0.4525 |
| 0.2005 | 2.1739 | 3500 | 0.4988 | 0.3129 |
| 0.1989 | 2.4845 | 4000 | 0.4852 | 0.4238 |
| 0.2155 | 2.7950 | 4500 | 0.4723 | 0.3675 |
| 0.1423 | 3.1056 | 5000 | 0.4926 | 0.2938 |
| 0.1136 | 3.4161 | 5500 | 0.5002 | 0.2962 |
| 0.1137 | 3.7267 | 6000 | 0.4891 | 0.2797 |
Framework versions
- Transformers 4.47.0.dev0
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3
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Model tree for abdouaziiz/whisper-v3-dyu4
Base model
openai/whisper-large-v3