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Whisper small TW - AlanDlink
This model is a fine-tuned version of openai/whisper-small on the Common Voice 15.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2175
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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 8000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.2151 | 1.33 | 1000 | 2.1197 |
| 0.5107 | 2.67 | 2000 | 0.4872 |
| 0.294 | 4.0 | 3000 | 0.2780 |
| 0.229 | 5.33 | 4000 | 0.2428 |
| 0.2193 | 6.67 | 5000 | 0.2278 |
| 0.2292 | 8.0 | 6000 | 0.2213 |
| 0.2288 | 9.33 | 7000 | 0.2184 |
| 0.2065 | 10.67 | 8000 | 0.2175 |
Framework versions
- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0
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openai/whisper-small