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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: 0.8800
- Wer: 0.8060
- Cer: 0.7585
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- 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 |
|---|---|---|---|---|---|
| 1.8904 | 1.32 | 100 | 1.5873 | 0.8893 | 0.5437 |
| 0.8039 | 2.63 | 200 | 0.9239 | 0.9076 | 0.5721 |
| 0.5988 | 3.95 | 300 | 0.7970 | 0.7850 | 0.4821 |
| 0.384 | 5.26 | 400 | 0.7586 | 0.7164 | 0.5206 |
| 0.2643 | 6.58 | 500 | 0.7578 | 0.9130 | 0.6843 |
| 0.2026 | 7.89 | 600 | 0.7627 | 0.9147 | 0.7228 |
| 0.1091 | 9.21 | 700 | 0.8043 | 0.8363 | 0.8283 |
| 0.0623 | 10.53 | 800 | 0.8342 | 0.7615 | 0.7619 |
| 0.0436 | 11.84 | 900 | 0.8577 | 0.7079 | 0.6824 |
| 0.0348 | 13.16 | 1000 | 0.8800 | 0.8060 | 0.7585 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.12.0+cu102
- Datasets 2.9.0
- Tokenizers 0.13.2
