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--- |
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base_model: openai/whisper-base |
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datasets: |
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- mozilla-foundation/common_voice_17_0 |
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language: |
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- nl |
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license: apache-2.0 |
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metrics: |
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- wer |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: Whisper Base NL |
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results: |
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- task: |
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type: automatic-speech-recognition |
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name: Automatic Speech Recognition |
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dataset: |
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name: Common Voice 17.0 |
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type: mozilla-foundation/common_voice_17_0 |
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config: nl |
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split: test |
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args: 'config: nl, split: test' |
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metrics: |
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- type: wer |
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value: 19.0031 |
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name: Wer |
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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 Base NL |
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This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Common Voice 17.0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.343928 |
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- Wer: 19.003155 |
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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: 32 |
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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: linear |
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- training_steps: 7500 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Step | Validation Loss | Wer | |
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|:-------------:|:----:|:---------------:|:-------:| |
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| 0.3639 | 500 | 0.396971 | 24.3028 | |
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| 0.2625 | 1000 | 0.358340 | 22.5210 | |
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| 0.2212 | 1500 | 0.341232 | 21.0322 | |
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| 0.1455 | 2000 | 0.330033 | 20.2046 | |
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| 0.1406 | 2500 | 0.324484 | 20.0508 | |
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| 0.1244 | 3000 | 0.321562 | 19.5279 | |
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| 0.0848 | 3500 | 0.321506 | 19.5114 | |
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| 0.0844 | 4000 | 0.316492 | 19.1462 | |
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| 0.0731 | 4500 | 0.321992 | 19.0167 | |
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| 0.0515 | 5000 | 0.324720 | 19.1492 | |
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| 0.0532 | 5500 | 0.324773 | 19.0148 | |
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| 0.0426 | 6000 | 0.332404 | 19.0576 | |
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| 0.0328 | 6500 | 0.334900 | 18.8249 | |
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| 0.0327 | 7000 | 0.335876 | 19.0080 | |
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| 0.0252 | 7500 | 0.343928 | 19.0031 | |
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### Framework versions |
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- Transformers 4.42.0.dev0 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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