Whisper Base Spanish - Chee Li
This model is a fine-tuned version of openai/whisper-base on the Google Fleurs dataset. It achieves the following results on the evaluation set:
- Loss: 0.3590
- Wer: 22.0101
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: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.5048 | 4.9751 | 1000 | 0.2942 | 16.3314 |
| 0.2077 | 9.9502 | 2000 | 0.3299 | 17.1524 |
| 0.0999 | 14.9254 | 3000 | 0.3504 | 19.7189 |
| 0.0614 | 19.9005 | 4000 | 0.3590 | 22.0101 |
Framework versions
- Transformers 4.43.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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