openai/whisper-medium
This model is a fine-tuned version of openai/whisper-medium on the common_voice_17_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.6413
- Wer: 36.1290
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: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0064 | 15.011 | 1000 | 0.5457 | 39.7097 |
| 0.0009 | 31.0094 | 2000 | 0.5771 | 38.3548 |
| 0.0 | 47.0078 | 3000 | 0.6180 | 36.4194 |
| 0.0 | 63.0062 | 4000 | 0.6349 | 36.0645 |
| 0.0 | 79.0046 | 5000 | 0.6413 | 36.1290 |
Framework versions
- Transformers 4.46.0.dev0
- Pytorch 2.5.0+cu118
- Datasets 3.0.3.dev0
- Tokenizers 0.20.1
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Base model
openai/whisper-medium