Whisper Tiny Hu v2
This model is a fine-tuned version of openai/whisper-tiny on the Common Voice 16.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.1930
- Wer Ortho: 17.3040
- Wer: 15.7367
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: 4e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 500
- training_steps: 15000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
---|---|---|---|---|---|
0.5487 | 0.33 | 1000 | 0.5970 | 55.5492 | 52.2206 |
0.3922 | 0.67 | 2000 | 0.4419 | 43.1109 | 39.9911 |
0.3242 | 1.0 | 3000 | 0.3662 | 37.2727 | 34.2040 |
0.2517 | 1.34 | 4000 | 0.3329 | 33.7890 | 30.8746 |
0.2455 | 1.67 | 5000 | 0.2925 | 30.6185 | 28.0196 |
0.1398 | 2.01 | 6000 | 0.2600 | 27.1709 | 24.5983 |
0.1421 | 2.34 | 7000 | 0.2491 | 26.1291 | 23.6347 |
0.1578 | 2.68 | 8000 | 0.2342 | 24.4761 | 22.0783 |
0.0732 | 3.01 | 9000 | 0.2163 | 22.1245 | 19.8547 |
0.0941 | 3.35 | 10000 | 0.2143 | 22.2058 | 19.8399 |
0.0936 | 3.68 | 11000 | 0.2094 | 20.5980 | 18.7756 |
0.0489 | 4.02 | 12000 | 0.2027 | 18.9630 | 17.2665 |
0.0548 | 4.35 | 13000 | 0.1981 | 18.4933 | 16.5491 |
0.0585 | 4.69 | 14000 | 0.1953 | 17.7195 | 15.7693 |
0.0356 | 5.02 | 15000 | 0.1930 | 17.3040 | 15.7367 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
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Model tree for Hungarians/whisper-tiny-cv16-hu-v2
Base model
openai/whisper-tiny
Finetuned
this model
Dataset used to train Hungarians/whisper-tiny-cv16-hu-v2
Evaluation results
- Wer on Common Voice 16.0 - Hungariantest set self-reported15.737