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: 1.8804
- Wer: 2.0146
- Cer: 1.4030
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 |
|---|---|---|---|---|---|
| 1.4622 | 16.67 | 100 | 1.5376 | 0.8662 | 0.7357 |
| 0.297 | 33.33 | 200 | 1.2979 | 0.8675 | 0.6481 |
| 0.0163 | 50.0 | 300 | 1.5699 | 1.4066 | 1.0449 |
| 0.0034 | 66.67 | 400 | 1.6919 | 1.6416 | 1.1817 |
| 0.0017 | 83.33 | 500 | 1.7654 | 1.6943 | 1.2587 |
| 0.0011 | 100.0 | 600 | 1.8153 | 1.9908 | 1.4084 |
| 0.0008 | 116.67 | 700 | 1.8455 | 1.9817 | 1.3867 |
| 0.0007 | 133.33 | 800 | 1.8647 | 2.0479 | 1.4215 |
| 0.0006 | 150.0 | 900 | 1.8764 | 2.0489 | 1.4253 |
| 0.0006 | 166.67 | 1000 | 1.8804 | 2.0146 | 1.4030 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.12.0+cu102
- Datasets 2.9.0
- Tokenizers 0.13.2
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