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Whisper large - Noc Operation
This model is a fine-tuned version of biodatlab/whisper-th-large-v3 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4602
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: 16
- seed: 42
- optimizer: Use paged_adamw_8bit 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: 10
- training_steps: 100
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.686 | 0.0631 | 25 | 0.4941 |
| 0.6964 | 0.1263 | 50 | 0.4734 |
| 0.6619 | 0.1894 | 75 | 0.4635 |
| 0.5732 | 0.2525 | 100 | 0.4602 |
Framework versions
- PEFT 0.17.0
- Transformers 4.48.0
- Pytorch 2.7.1+cu128
- Datasets 3.6.0
- Tokenizers 0.21.4
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Base model
biodatlab/whisper-th-large-v3