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Whisper Small Synthesized Turkish
This model is a fine-tuned version of openai/whisper-small on the synthesized_squad dataset. It achieves the following results on the evaluation set:
- Loss: 0.2564
- Wer: 13.7267
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: 8
- 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: 2000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
1.276 | 1.04 | 100 | 0.5859 | 92.8836 |
0.436 | 2.08 | 200 | 0.3916 | 19.5285 |
0.218 | 3.12 | 300 | 0.2345 | 13.2453 |
0.0903 | 4.17 | 400 | 0.2332 | 12.9737 |
0.0517 | 5.21 | 500 | 0.2360 | 14.3439 |
0.0302 | 6.25 | 600 | 0.2318 | 14.0415 |
0.0223 | 7.29 | 700 | 0.2372 | 13.9674 |
0.0085 | 8.33 | 800 | 0.2421 | 12.4738 |
0.0084 | 9.38 | 900 | 0.2424 | 12.3750 |
0.0043 | 10.42 | 1000 | 0.2421 | 12.8935 |
0.0034 | 11.46 | 1100 | 0.2478 | 13.6218 |
0.0025 | 12.5 | 1200 | 0.2490 | 14.7327 |
0.002 | 13.54 | 1300 | 0.2513 | 13.0910 |
0.0019 | 14.58 | 1400 | 0.2521 | 13.2453 |
0.0013 | 15.62 | 1500 | 0.2532 | 13.2144 |
0.0012 | 16.67 | 1600 | 0.2547 | 13.3132 |
0.001 | 17.71 | 1700 | 0.2552 | 13.7514 |
0.001 | 18.75 | 1800 | 0.2559 | 13.7452 |
0.001 | 19.79 | 1900 | 0.2563 | 13.7514 |
0.001 | 20.83 | 2000 | 0.2564 | 13.7267 |
Framework versions
- Transformers 4.28.0.dev0
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3