Whisper Small Ori vi
This model is a fine-tuned version of openai/whisper-small on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 3.0544
- Wer: 66.3191
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: 0.0005
- train_batch_size: 16
- eval_batch_size: 8
- 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: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.7932 | 2.2222 | 1000 | 3.2617 | 90.6510 |
| 0.5752 | 4.4444 | 2000 | 3.0216 | 78.4995 |
| 0.1394 | 6.6667 | 3000 | 3.0541 | 70.0196 |
| 0.0175 | 8.8889 | 4000 | 3.0544 | 66.3191 |
Framework versions
- Transformers 4.46.1
- Pytorch 2.4.0
- Datasets 3.1.0
- Tokenizers 0.20.0
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Base model
openai/whisper-small