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Whisper Medium
This model is a fine-tuned version of openai/whisper-medium on the easycall-v2 dataset. It achieves the following results on the evaluation set:
- Loss: 0.0410
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: 5e-05
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.0945 | 1.0 | 2139 | 0.0703 |
| 0.0417 | 2.0 | 4278 | 0.0497 |
| 0.0291 | 3.0 | 6417 | 0.0424 |
| 0.0184 | 3.9984 | 8552 | 0.0410 |
Framework versions
- PEFT 0.14.0
- Transformers 4.48.1
- Pytorch 2.2.2+cu121
- Datasets 2.19.2
- Tokenizers 0.21.0
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Base model
openai/whisper-medium