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
- Downloads last month
- 14
This model does not have enough activity to be deployed to Inference API (serverless) yet.
Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
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