Whisper Medium Uzbek
This model is a fine-tuned version of openai/whisper-medium on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.4148
- Wer: 38.1999
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: 3e-05
- train_batch_size: 64
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.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: 200
- training_steps: 1500
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.6553 | 0.5330 | 250 | 0.5830 | 51.2637 |
0.3945 | 1.0661 | 500 | 0.4612 | 41.6914 |
0.3352 | 1.5991 | 750 | 0.4360 | 42.0931 |
0.2028 | 2.1322 | 1000 | 0.4155 | 38.1133 |
0.1956 | 2.6652 | 1250 | 0.4081 | 37.6900 |
0.1202 | 3.1983 | 1500 | 0.4148 | 38.1999 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0
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