<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->
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: 2.1975
- Wer: 1.6817
- Cer: 1.2800
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 |
|---|---|---|---|---|---|
| 1.5514 | 33.31 | 100 | 1.6389 | 0.8196 | 0.8754 |
| 0.1703 | 66.62 | 200 | 1.6896 | 1.0058 | 0.6987 |
| 0.0039 | 99.92 | 300 | 1.9380 | 1.7011 | 1.1631 |
| 0.0015 | 133.31 | 400 | 2.0324 | 1.6950 | 1.2498 |
| 0.0008 | 166.62 | 500 | 2.0957 | 1.4898 | 1.0992 |
| 0.0005 | 199.92 | 600 | 2.1417 | 1.7320 | 1.2528 |
| 0.0004 | 233.31 | 700 | 2.1681 | 1.6077 | 1.1845 |
| 0.0003 | 266.62 | 800 | 2.1847 | 1.625 | 1.2008 |
| 0.0003 | 299.92 | 900 | 2.1944 | 1.6515 | 1.2196 |
| 0.0003 | 333.31 | 1000 | 2.1975 | 1.6817 | 1.2800 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.12.0+cu102
- Datasets 2.9.0
- Tokenizers 0.13.2
