Whisper Base Ru
This model is a fine-tuned version of openai/whisper-base on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3220
- Wer: 26.0941
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
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.3017 | 0.9847 | 1000 | 0.3557 | 28.9880 |
| 0.2071 | 1.9695 | 2000 | 0.3259 | 26.9671 |
| 0.1581 | 2.9542 | 3000 | 0.3197 | 26.2272 |
| 0.1152 | 3.9389 | 4000 | 0.3220 | 26.0941 |
Framework versions
- Transformers 4.41.0
- Pytorch 2.0.1+cu118
- Datasets 2.19.1
- Tokenizers 0.19.1
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openai/whisper-base