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--- |
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license: apache-2.0 |
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tags: |
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- whisper-event |
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- generated_from_trainer |
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datasets: |
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- kul-speech-lab/CGN |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Large CGN |
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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: kul-speech-lab/CGN |
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type: kul-speech-lab/CGN |
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config: cgn-dev.py |
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split: test |
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metrics: |
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- name: Wer |
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type: wer |
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value: 9.6159 |
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--- |
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# Whisper Large CGN |
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This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the kul-speech-lab/CGN dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.23932012915611267 |
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- Wer: 9.615871912312803 |
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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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- eval_batch_size: 16 |
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- gradient_accumulation_steps: 2 |
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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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- lr_scheduler_warmup_steps: 500 |
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- training_steps: 15000 |
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- mixed_precision_training: Native AMP |
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### Framework versions |
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- Transformers 4.26.0.dev0 |
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- Pytorch 1.13.0 |
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- Datasets 2.7.1.dev0 |
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- Tokenizers 0.13.2 |
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Whisper large model finetuned on Flemish part of Corpus Gesproken Nederlands (CGN). |
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