Whisper-small - Huang Jordan
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: 0.2699
- Cer: 11.8994
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: 3e-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: 50
- training_steps: 400
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|---|---|---|---|---|
| 0.296 | 0.2445 | 100 | 0.3856 | 16.0790 |
| 0.2479 | 0.4890 | 200 | 0.3302 | 13.9624 |
| 0.2008 | 0.7335 | 300 | 0.2908 | 12.4704 |
| 0.1787 | 0.9780 | 400 | 0.2699 | 11.8994 |
Framework versions
- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
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Base model
openai/whisper-small