Whisper Large fine tuned
This model is a fine-tuned version of openai/whisper-large on the 1620 RAW dataset. It achieves the following results on the evaluation set:
- Loss: 0.1902
- Wer: 12.3332
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: 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: 500
- training_steps: 750
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0375 | 2.4691 | 200 | 0.1497 | 13.3916 |
| 0.0174 | 4.9383 | 400 | 0.1739 | 12.7934 |
| 0.0114 | 7.4074 | 600 | 0.1902 | 12.3332 |
Framework versions
- Transformers 4.48.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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Model tree for Mohsen21/WHISPERLARGEUAE
Base model
openai/whisper-large