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Whisper Small Turkish
This model is a fine-tuned version of openai/whisper-small on the mozilla-foundation/common_voice_11_0 tr dataset. It achieves the following results on the evaluation set:
- Loss: 0.2576
- Wer: 16.6327
- Cer: 4.2853
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: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 0.1412 | 0.08 | 400 | 0.2656 | 19.8335 | 5.2393 |
| 0.0851 | 1.03 | 800 | 0.2382 | 18.6300 | 4.8916 |
| 0.0525 | 1.11 | 1200 | 0.2532 | 19.1696 | 5.2238 |
| 0.0163 | 2.07 | 1600 | 0.2447 | 17.2014 | 4.5840 |
| 0.0202 | 3.02 | 2000 | 0.2472 | 17.1063 | 4.4935 |
| 0.0075 | 3.1 | 2400 | 0.2503 | 17.0151 | 4.4318 |
| 0.0039 | 4.05 | 2800 | 0.2514 | 16.7433 | 4.3655 |
| 0.0038 | 5.01 | 3200 | 0.2565 | 16.8870 | 4.3582 |
| 0.0023 | 5.09 | 3600 | 0.2590 | 16.6987 | 4.3337 |
| 0.0013 | 6.04 | 4000 | 0.2576 | 16.6327 | 4.2853 |
| 0.0011 | 6.12 | 4400 | 0.2647 | 16.9122 | 4.3556 |
| 0.001 | 7.07 | 4800 | 0.2615 | 16.6346 | 4.2839 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.8.1.dev0
- Tokenizers 0.13.2
