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Whisper
This model is a fine-tuned version of openai/whisper-large-v2 on the immunology dataset dataset. It achieves the following results on the evaluation set:
- Loss: 0.2365
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.2374 | 1.0 | 440 | 0.2727 |
| 0.1471 | 2.0 | 880 | 0.2464 |
| 0.1188 | 3.0 | 1320 | 0.2365 |
Framework versions
- PEFT 0.8.2
- Transformers 4.39.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
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Model tree for shg1421/whisper-medium-peft
Base model
openai/whisper-small