<!-- 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: 2.0552
- Wer: 1.3802
- Cer: 0.8297
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 |
|---|---|---|---|---|---|
| 1.3477 | 33.33 | 100 | 1.8981 | 1.2433 | 0.8110 |
| 0.0238 | 66.67 | 200 | 1.7919 | 0.9340 | 0.5818 |
| 0.0032 | 100.0 | 300 | 1.8780 | 0.9756 | 0.6155 |
| 0.0014 | 133.33 | 400 | 1.9332 | 1.3582 | 0.8039 |
| 0.0008 | 166.67 | 500 | 1.9769 | 1.6333 | 0.9329 |
| 0.0005 | 200.0 | 600 | 2.0099 | 1.3790 | 0.8230 |
| 0.0004 | 233.33 | 700 | 2.0307 | 1.3851 | 0.8270 |
| 0.0004 | 266.67 | 800 | 2.0442 | 1.3851 | 0.8286 |
| 0.0003 | 300.0 | 900 | 2.0523 | 1.3814 | 0.8303 |
| 0.0003 | 333.33 | 1000 | 2.0552 | 1.3802 | 0.8297 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.12.0+cu102
- Datasets 2.9.0
- Tokenizers 0.13.2
