Whisper Small Spanish
This model is a fine-tuned version of openai/whisper-small on the CIEMPIESS dataset. It achieves the following results on the evaluation set:
- Loss: 0.0152
- Wer: 0.3845
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: 16
- 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: 500
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2277 | 0.4484 | 100 | 0.2420 | 9.5187 |
| 0.2788 | 0.8969 | 200 | 0.1965 | 7.9300 |
| 0.1799 | 1.3453 | 300 | 0.1541 | 6.9804 |
| 0.158 | 1.7937 | 400 | 0.1121 | 5.4762 |
| 0.0926 | 2.2422 | 500 | 0.0810 | 4.1792 |
| 0.0912 | 2.6906 | 600 | 0.0584 | 3.7438 |
| 0.0451 | 3.1390 | 700 | 0.0364 | 2.4318 |
| 0.0416 | 3.5874 | 800 | 0.0261 | 1.3271 |
| 0.0312 | 4.0359 | 900 | 0.0178 | 0.4736 |
| 0.015 | 4.4843 | 1000 | 0.0152 | 0.3845 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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