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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- wer |
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model-index: |
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- name: openai/whisper-medium-en |
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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: myst-test |
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type: asr |
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config: en |
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split: test |
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metrics: |
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- type: wer |
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value: 8.85 |
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name: WER |
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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: cslu_scripted |
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type: asr |
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config: en |
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split: test |
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metrics: |
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- type: wer |
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value: 2.38 |
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name: WER |
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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: cslu_spontaneous |
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type: asr |
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config: en |
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split: test |
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metrics: |
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- type: wer |
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value: 16.53 |
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name: WER |
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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: librispeech |
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type: asr |
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config: en |
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split: testclean |
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metrics: |
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- type: wer |
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value: 3.52 |
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name: WER |
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--- |
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# openai/whisper-medium-en |
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This model is a fine-tuned version of [openai/whisper-medium-en](https://huggingface.co/openai/whisper-medium-en) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.22987066209316254 |
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- Wer: 7.945455976651671` |
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## Training and evaluation data |
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- Training data: Myst Train (125 hours) + CSLU Scripted train (35 hours) |
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- Evaluation data: Myst Dev (20.9 hours) + CSLU Scripted Dev(4.8) |
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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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- 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: 10000 |
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- converged_after: 1000 |
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