Whisper Small - Chee Li
This model is a fine-tuned version of openai/whisper-small on the Google Fleurs dataset. It achieves the following results on the evaluation set:
- Loss: 0.2891
- Wer: 25.9334
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 |
|---|---|---|---|---|
| 0.0097 | 5.5866 | 1000 | 0.2532 | 24.5100 |
| 0.0011 | 11.1732 | 2000 | 0.2725 | 21.6164 |
| 0.0006 | 16.7598 | 3000 | 0.2845 | 24.3311 |
| 0.0005 | 22.3464 | 4000 | 0.2891 | 25.9334 |
Framework versions
- Transformers 4.44.0
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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openai/whisper-small