Whisper Small Kur - Rizgan Gerdenzeri
This model is a fine-tuned version of openai/whisper-small on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.5986
- Wer: 35.2686
Model description
More information needed
Intended uses & limitations
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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: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.3355 | 1.7699 | 1000 | 0.4746 | 40.3146 |
| 0.0921 | 3.5398 | 2000 | 0.4746 | 36.7845 |
| 0.0142 | 5.3097 | 3000 | 0.5598 | 36.6251 |
| 0.004 | 7.0796 | 4000 | 0.5986 | 35.2686 |
Framework versions
- Transformers 4.43.3
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Base model
openai/whisper-small