Whisper small pt jwlang - Michel Mesquita
This model is a fine-tuned version of openai/whisper-small on the jwlang 1.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.6913
- Wer: 23.2558
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 |
|---|---|---|---|---|
| 0.0053 | 14.0845 | 1000 | 0.6128 | 22.3990 |
| 0.0002 | 28.1690 | 2000 | 0.6528 | 22.6438 |
| 0.0001 | 42.2535 | 3000 | 0.6806 | 23.0110 |
| 0.0001 | 56.3380 | 4000 | 0.6913 | 23.2558 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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openai/whisper-small