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base Turkish Whisper (bTW)
This model is a fine-tuned version of openai/whisper-base on the Ermetal Meetings dataset. It achieves the following results on the evaluation set:
- Loss: 1.5006
- Wer: 1.3698
- Cer: 1.1255
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: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- 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 | Cer |
|---|---|---|---|---|---|
| 1.8141 | 5.53 | 100 | 1.4784 | 0.7680 | 0.4463 |
| 0.673 | 11.11 | 200 | 1.0561 | 0.8175 | 0.5889 |
| 0.2762 | 16.64 | 300 | 1.0746 | 0.8564 | 0.5887 |
| 0.0852 | 22.21 | 400 | 1.2061 | 1.4290 | 0.9567 |
| 0.0199 | 27.75 | 500 | 1.2649 | 1.0706 | 0.9168 |
| 0.0087 | 33.32 | 600 | 1.4641 | 1.2417 | 1.0328 |
| 0.0041 | 38.85 | 700 | 1.4685 | 1.2806 | 0.9546 |
| 0.003 | 44.43 | 800 | 1.4830 | 1.3633 | 1.0236 |
| 0.0026 | 49.96 | 900 | 1.4964 | 1.3698 | 1.0375 |
| 0.0025 | 55.53 | 1000 | 1.5006 | 1.3698 | 1.1255 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.12.0+cu102
- Datasets 2.9.0
- Tokenizers 0.13.2
