Whisper Medium UZ - AbdulxoliqMirzaev
This model is a fine-tuned version of openai/whisper-medium on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0640
- Wer: 6.8956
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 OptimizerNames.ADAMW_TORCH_FUSED 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 |
|---|---|---|---|---|
| 0.2112 | 0.16 | 500 | 0.2028 | 19.4923 |
| 0.1119 | 0.32 | 1000 | 0.1140 | 11.7691 |
| 0.0792 | 0.48 | 1500 | 0.0757 | 7.8866 |
| 0.0689 | 0.64 | 2000 | 0.0640 | 6.8956 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.9.0+cu128
- Datasets 4.3.0
- Tokenizers 0.22.1
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Model tree for AbdulxoliqMirzaev/whisper-uz-medium
Base model
openai/whisper-medium