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whisper-medium-loz
This model is a fine-tuned version of openai/whisper-medium on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7116
- Wer: 83.0853
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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- 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 |
|---|---|---|---|---|
| 2.5661 | 1.08 | 500 | 2.4638 | 75.4238 |
| 0.7885 | 2.16 | 1000 | 1.5264 | 57.4479 |
| 0.5592 | 3.23 | 1500 | 1.3387 | 56.4385 |
| 0.3583 | 4.31 | 2000 | 1.1329 | 62.6116 |
| 0.2569 | 5.39 | 2500 | 0.7550 | 84.4700 |
| 0.1977 | 6.47 | 3000 | 0.6823 | 97.2564 |
| 0.1697 | 7.54 | 3500 | 0.7048 | 89.2584 |
| 0.1754 | 8.62 | 4000 | 0.7116 | 83.0853 |
Framework versions
- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2
