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--- |
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language: |
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- hu |
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license: apache-2.0 |
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base_model: openai/whisper-medium |
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tags: |
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- generated_from_trainer |
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datasets: |
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- mozilla-foundation/common_voice_13_0 |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Medium HU |
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results: |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: Common Voice 13 |
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type: mozilla-foundation/common_voice_13_0 |
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config: hu |
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split: test |
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args: hu |
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metrics: |
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- name: Wer |
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type: wer |
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value: 14.829034193161366 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# Whisper Medium HU |
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Common Voice 13 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2699 |
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- Wer Ortho: 17.1763 |
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- Wer: 14.8290 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: constant_with_warmup |
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- lr_scheduler_warmup_steps: 50 |
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- training_steps: 20000 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer | |
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|:-------------:|:-----:|:-----:|:---------------:|:---------:|:-------:| |
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| 0.0804 | 1.38 | 2000 | 0.1977 | 19.2869 | 16.6612 | |
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| 0.038 | 2.76 | 4000 | 0.2028 | 18.2211 | 15.7494 | |
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| 0.014 | 4.14 | 6000 | 0.2190 | 17.9961 | 15.3466 | |
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| 0.0107 | 5.51 | 8000 | 0.2328 | 17.3490 | 14.9370 | |
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| 0.0144 | 6.89 | 10000 | 0.2376 | 17.4153 | 14.9559 | |
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| 0.0049 | 8.27 | 12000 | 0.2424 | 16.9984 | 14.6953 | |
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| 0.0071 | 9.65 | 14000 | 0.2594 | 17.6961 | 15.3586 | |
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| 0.0037 | 11.03 | 16000 | 0.2546 | 17.2007 | 14.8667 | |
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| 0.0078 | 12.41 | 18000 | 0.2644 | 17.5757 | 15.1495 | |
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| 0.0043 | 13.78 | 20000 | 0.2699 | 17.1763 | 14.8290 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.2.0 |
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- Datasets 2.17.0 |
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- Tokenizers 0.15.2 |
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