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whisper-synthesized-turkish-8-hour-hlr
This model is a fine-tuned version of openai/whisper-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3824
- Wer: 49.2902
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: 0.0001
- 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: 4000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.7481 | 0.52 | 100 | 0.2675 | 14.6834 |
0.1975 | 1.04 | 200 | 0.2534 | 13.2144 |
0.1388 | 1.56 | 300 | 0.2755 | 15.6647 |
0.1585 | 2.08 | 400 | 0.3080 | 14.6649 |
0.1153 | 2.6 | 500 | 0.3421 | 17.7447 |
0.1241 | 3.12 | 600 | 0.3570 | 16.8189 |
0.1093 | 3.65 | 700 | 0.3776 | 18.8125 |
0.09 | 4.17 | 800 | 0.3859 | 30.0518 |
0.0751 | 4.69 | 900 | 0.3874 | 17.3929 |
0.0758 | 5.21 | 1000 | 0.3987 | 20.0901 |
0.0602 | 5.73 | 1100 | 0.4017 | 17.1460 |
0.0568 | 6.25 | 1200 | 0.3824 | 15.6154 |
0.0454 | 6.77 | 1300 | 0.3926 | 15.8808 |
0.0433 | 7.29 | 1400 | 0.4146 | 16.3869 |
0.0341 | 7.81 | 1500 | 0.4078 | 16.1153 |
0.0295 | 8.33 | 1600 | 0.4192 | 17.1275 |
0.0274 | 8.85 | 1700 | 0.4140 | 16.3745 |
0.0246 | 9.38 | 1800 | 0.4077 | 21.0344 |
0.0211 | 9.9 | 1900 | 0.4003 | 19.8741 |
0.0149 | 10.42 | 2000 | 0.4054 | 108.7335 |
0.0172 | 10.94 | 2100 | 0.3917 | 20.6024 |
0.0138 | 11.46 | 2200 | 0.3942 | 889.4643 |
0.0108 | 11.98 | 2300 | 0.3906 | 55.0673 |
0.0099 | 12.5 | 2400 | 0.3834 | 29.9778 |
0.0067 | 13.02 | 2500 | 0.3947 | 34.5883 |
0.0045 | 13.54 | 2600 | 0.3940 | 20.9789 |
0.0035 | 14.06 | 2700 | 0.3911 | 15.6462 |
0.0031 | 14.58 | 2800 | 0.3905 | 18.3990 |
0.0018 | 15.1 | 2900 | 0.3919 | 16.3190 |
0.0011 | 15.62 | 3000 | 0.3906 | 18.0286 |
0.001 | 16.15 | 3100 | 0.3911 | 17.6521 |
0.0006 | 16.67 | 3200 | 0.3813 | 27.6879 |
0.0007 | 17.19 | 3300 | 0.3800 | 45.7536 |
0.0003 | 17.71 | 3400 | 0.3805 | 51.2529 |
0.0001 | 18.23 | 3500 | 0.3815 | 51.7282 |
0.0001 | 18.75 | 3600 | 0.3821 | 47.0065 |
0.0002 | 19.27 | 3700 | 0.3821 | 45.8585 |
0.0001 | 19.79 | 3800 | 0.3823 | 47.7904 |
0.0001 | 20.31 | 3900 | 0.3824 | 49.2594 |
0.0003 | 20.83 | 4000 | 0.3824 | 49.2902 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3