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---
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
should probably proofread and complete it, then remove this comment. -->
# 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
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