---
language:
- dv
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: dysarthria_emo_enhancer_0_1
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: custom_torgo_0_0 + UASpeech
      type: mozilla-foundation/common_voice_13_0
    metrics:
    - name: Wer
      type: wer
      value: 46.389067073277616
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# dysarthria_emo_enhancer_0_0

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.
It achieves the following results on the evaluation set:
- Wer: 34.5269
- Wer Ortho: 36.0478

And the following results on the TORGO + UAS training set:
- Acc: 0.68
- Wer: 32.28

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 8
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 500

### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1