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fine_tuned_sample
This model is a fine-tuned version of openai/whisper-large-v2 on the common_voice_17_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.1107
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: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
1.2918 | 1.0 | 1728 | 1.1855 |
0.8603 | 2.0 | 3456 | 0.6720 |
0.4763 | 3.0 | 5184 | 0.3180 |
0.1549 | 4.0 | 6912 | 0.1107 |
Framework versions
- PEFT 0.13.3.dev0
- Transformers 4.47.0.dev0
- Pytorch 2.5.0+cu121
- Datasets 3.0.2
- Tokenizers 0.20.1
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openai/whisper-large-v2