Whisper base uz - Jamshid Ahmadov
This model is a fine-tuned version of jamshidahmadov/whisper-uz on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1652
- Wer: 14.0135
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: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- 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: 500
- training_steps: 2000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.0346 | 0.5714 | 500 | 0.1719 | 14.7950 |
0.0348 | 1.1429 | 1000 | 0.1703 | 14.2490 |
0.0327 | 1.7143 | 1500 | 0.1672 | 14.1848 |
0.02 | 2.2857 | 2000 | 0.1652 | 14.0135 |
Framework versions
- Transformers 4.50.3
- Pytorch 2.5.1+cu121
- Datasets 3.5.0
- Tokenizers 0.21.0
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