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whosper-large
This model is a fine-tuned version of openai/whisper-large-v2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4371
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
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- 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
- lr_scheduler_warmup_steps: 50
- num_epochs: 6
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 3.0514 | 1.0 | 1732 | 0.6824 |
| 2.2658 | 2.0 | 3464 | 0.5998 |
| 2.0274 | 3.0 | 5196 | 0.5282 |
| 1.48 | 4.0 | 6928 | 0.4793 |
| 1.1693 | 5.0 | 8660 | 0.4441 |
| 0.8762 | 5.9970 | 10386 | 0.4371 |
Framework versions
- PEFT 0.14.1.dev0
- Transformers 4.48.0.dev0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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Model tree for sudoping01/whosper-large
Base model
openai/whisper-large-v2