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whisper-large-v3-MH-fine-tuned
This model is a fine-tuned version of openai/whisper-large-v3 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6099
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: 4
- 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: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.0586 | 1.0 | 4 | 0.8056 |
| 1.0643 | 2.0 | 8 | 0.6915 |
| 0.7456 | 3.0 | 12 | 0.6105 |
| 0.6496 | 4.0 | 16 | 0.5754 |
| 0.6013 | 5.0 | 20 | 0.5447 |
| 0.443 | 6.0 | 24 | 0.5263 |
| 0.3267 | 7.0 | 28 | 0.5356 |
| 0.2908 | 8.0 | 32 | 0.5291 |
| 0.1509 | 9.0 | 36 | 0.5256 |
| 0.1156 | 10.0 | 40 | 0.5158 |
| 0.0715 | 11.0 | 44 | 0.5315 |
| 0.0516 | 12.0 | 48 | 0.5286 |
| 0.0457 | 13.0 | 52 | 0.5434 |
| 0.048 | 14.0 | 56 | 0.5550 |
| 0.0297 | 15.0 | 60 | 0.5781 |
| 0.0213 | 16.0 | 64 | 0.5890 |
| 0.0198 | 17.0 | 68 | 0.6000 |
| 0.0175 | 18.0 | 72 | 0.6046 |
| 0.0158 | 19.0 | 76 | 0.6101 |
| 0.0128 | 20.0 | 80 | 0.6099 |
Framework versions
- PEFT 0.11.2.dev0
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for Aysha630/whisper-large-v3-MH-fine-tuned
Base model
openai/whisper-large-v3