ft_model
This model is a fine-tuned version of openai/whisper-small on the EBRC dataset. It achieves the following results on the evaluation set:
- Loss: 0.2978
- Cer: 10.5708
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: 5e-05
- train_batch_size: 32
- eval_batch_size: 16
- 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: 6000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|---|---|---|---|---|
| 0.3829 | 1.0 | 1500 | 0.3817 | 15.4574 |
| 0.1779 | 2.0 | 3000 | 0.3238 | 13.5614 |
| 0.0732 | 3.0 | 4500 | 0.2954 | 11.2004 |
| 0.0228 | 4.0 | 6000 | 0.2978 | 10.5708 |
Framework versions
- Transformers 4.42.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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Base model
openai/whisper-small