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Whisper Large v3 Thai Finetuned
This model is a fine-tuned version of openai/whisper-large-v3 on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.1197
- Cer: 347.2750
- Wer: 37.2841
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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use paged_adamw_8bit with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.01
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer | Wer |
|---|---|---|---|---|---|
| 0.1468 | 1.0 | 2052 | 0.1265 | 348.7140 | 42.3821 |
| 0.1225 | 2.0 | 4104 | 0.1178 | 387.4029 | 34.6267 |
| 0.0914 | 3.0 | 6156 | 0.1157 | 368.2561 | 36.4184 |
| 0.0779 | 4.0 | 8208 | 0.1182 | 347.7405 | 36.8434 |
| 0.0624 | 5.0 | 10260 | 0.1197 | 347.2750 | 37.2841 |
Framework versions
- PEFT 0.14.1.dev0
- Transformers 4.49.0.dev0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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Base model
openai/whisper-large-v3