Whisper Base Ml Ru
This model is a fine-tuned version of openai/whisper-base on the ML датасет dataset. It achieves the following results on the evaluation set:
- Loss: 0.4705
- Wer: 35.2729
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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.6752 | 0.6649 | 250 | 0.6513 | 39.3404 |
| 0.4415 | 1.3298 | 500 | 0.5277 | 38.4923 |
| 0.4037 | 1.9947 | 750 | 0.4766 | 35.0766 |
| 0.2825 | 2.6596 | 1000 | 0.4705 | 35.2729 |
Framework versions
- Transformers 4.41.0
- Pytorch 2.0.1+cu118
- Datasets 2.19.1
- Tokenizers 0.19.1
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