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: 1.0576
- Wer: 1.1825
- Cer: 1.0651
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 |
|---|---|---|---|---|---|
| 1.6978 | 3.33 | 100 | 1.3610 | 0.7852 | 0.4184 |
| 0.6547 | 6.66 | 200 | 0.8659 | 0.7226 | 0.4379 |
| 0.3805 | 9.99 | 300 | 0.8060 | 0.7256 | 0.4330 |
| 0.1886 | 13.33 | 400 | 0.8382 | 0.6395 | 0.4164 |
| 0.0745 | 16.66 | 500 | 0.9106 | 0.8185 | 0.6747 |
| 0.0303 | 19.99 | 600 | 0.9697 | 0.8509 | 0.5685 |
| 0.0139 | 23.33 | 700 | 1.0096 | 0.8773 | 0.6483 |
| 0.0069 | 26.66 | 800 | 1.0367 | 1.2781 | 1.2923 |
| 0.0054 | 29.99 | 900 | 1.0518 | 1.2363 | 1.1066 |
| 0.0048 | 33.33 | 1000 | 1.0576 | 1.1825 | 1.0651 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.12.0+cu102
- Datasets 2.9.0
- Tokenizers 0.13.2