base
This model is a fine-tuned version of openai/whisper-large-v3 on the tutorial Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.4640
- Wer: 87.2070
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: 8
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- 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: 3000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.3195 | 0.8 | 1000 | 0.5051 | 53.9286 |
| 0.1643 | 1.6 | 2000 | 0.4609 | 62.1667 |
| 0.09 | 2.4 | 3000 | 0.4640 | 87.2070 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
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