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--- |
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language: |
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- dv |
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license: apache-2.0 |
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base_model: openai/whisper-small |
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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: dysarthria_emo_enhancer_0_1 |
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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: custom_torgo_0_0 + UASpeech |
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type: mozilla-foundation/common_voice_13_0 |
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metrics: |
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- name: Wer |
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type: wer |
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value: 46.389067073277616 |
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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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# dysarthria_emo_enhancer_0_0 |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the custom_torgo_0_0 dataset merged with the UASpeech dataset. |
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It achieves the following results on the evaluation set: |
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- Wer: 34.5269 |
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- Wer Ortho: 36.0478 |
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And the following results on the TORGO + UAS training set: |
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- Acc: 0.68 |
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- Wer: 32.28 |
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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: 8 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 16 |
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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: 500 |
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### Framework versions |
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- Transformers 4.34.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.1 |
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