README.md

metadata

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

dysarthria_emo_enhancer_0_0

This model is a fine-tuned version of 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