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Whisper Small ha Test- Dinaka Ezeani
This model is a fine-tuned version of openai/whisper-medium on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 1.4394
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: 64
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2
- training_steps: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 3.5742 | 0.0323 | 1 | 2.8898 |
| 3.6442 | 0.0645 | 2 | 2.5929 |
| 3.3101 | 0.0968 | 3 | 2.1882 |
| 2.797 | 0.1290 | 4 | 1.9838 |
| 2.6471 | 0.1613 | 5 | 1.7828 |
| 2.3832 | 0.1935 | 6 | 1.6560 |
| 2.1674 | 0.2258 | 7 | 1.5718 |
| 2.0717 | 0.2581 | 8 | 1.5056 |
| 2.0157 | 0.2903 | 9 | 1.4620 |
| 1.9508 | 0.3226 | 10 | 1.4394 |
Framework versions
- PEFT 0.12.0
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1
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openai/whisper-medium