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Whisper Turbo Multilingual
This model is a fine-tuned version of openai/whisper-large-v3-turbo on the custom_multilingual dataset. It achieves the following results on the evaluation set:
- Loss: 0.4791
- Wer: 18.75
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: 0.001
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5
- training_steps: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.3929 | 1.0 | 10 | 0.7320 | 21.875 |
| 0.076 | 2.0 | 20 | 0.4791 | 18.75 |
Framework versions
- PEFT 0.15.2.dev0
- Transformers 4.46.3
- Pytorch 2.3.1+cu121
- Datasets 3.0.0
- Tokenizers 0.20.3
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