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Whisper-small-Ar-MDD
This model is a fine-tuned version of openai/whisper-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2212
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: 6
- eval_batch_size: 6
- 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: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.0726 | 1.0 | 546 | 0.2210 |
| 0.0419 | 2.0 | 1092 | 0.2139 |
| 0.0322 | 3.0 | 1638 | 0.1935 |
| 0.0175 | 4.0 | 2184 | 0.1896 |
| 0.0266 | 5.0 | 2730 | 0.1927 |
| 0.0178 | 6.0 | 3276 | 0.2013 |
| 0.0081 | 7.0 | 3822 | 0.1979 |
| 0.0081 | 8.0 | 4368 | 0.2113 |
| 0.0018 | 9.0 | 4914 | 0.2146 |
| 0.0015 | 10.0 | 5460 | 0.2212 |
Framework versions
- PEFT 0.10.0
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for nrshoudi/Whisper-small-Ar-MDD
Base model
openai/whisper-small