Whisper Medium Turkish
This model is a fine-tuned version of openai/whisper-medium on the mozilla-foundation/common_voice_11_0 Turkish dataset. It achieves the following results on the evaluation set:
- Loss: 0.1879
- Wer: 10.5033
Model description
The model is fine-tuned for 1000 steps/updates. - Zero-shot - 20.89 (CV11) - Fine-tune on CV11 - 10.50 (CV11) (-49%)
- Zeroshot - 10.4 (Google Fluers)
- Fine-tune on CV11 - 9.26 (Google Fluers)
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: 32
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- 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 |
|---|---|---|---|---|
| 0.0348 | 3.05 | 1000 | 0.1879 | 10.5033 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
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Dataset used to train sgangireddy/whisper-medium-tr
Space using sgangireddy/whisper-medium-tr 1
Evaluation results
- Wer on mozilla-foundation/common_voice_11_0 trtest set self-reported10.503