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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: 1.4238
- Wer: 0.9367
- Cer: 0.7611
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 |
|---|---|---|---|---|---|
| 1.6918 | 2.85 | 100 | 1.5023 | 0.7940 | 0.4289 |
| 0.6823 | 5.71 | 200 | 1.0475 | 0.8783 | 0.5573 |
| 0.4277 | 8.57 | 300 | 0.9944 | 0.8054 | 0.6120 |
| 0.2244 | 11.43 | 400 | 1.0460 | 0.6878 | 0.3825 |
| 0.1138 | 14.28 | 500 | 1.2059 | 0.7510 | 0.5020 |
| 0.0468 | 17.14 | 600 | 1.2180 | 1.1436 | 1.0719 |
| 0.0193 | 19.99 | 700 | 1.2801 | 1.1500 | 0.9344 |
| 0.0093 | 22.85 | 800 | 1.4574 | 0.9238 | 0.6799 |
| 0.0068 | 25.71 | 900 | 1.4137 | 0.9400 | 0.8128 |
| 0.0062 | 28.57 | 1000 | 1.4238 | 0.9367 | 0.7611 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.12.0+cu102
- Datasets 2.9.0
- Tokenizers 0.13.2
