transformers pytorch whisper automatic-speech-recognition generated_from_trainer dv dataset:mozilla-foundation/common_voice_13_0 base_model:openai/whisper-small license:apache-2.0 model-index endpoints_compatible region:us
---
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_0
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: custom_torgo_0_0
      type: mozilla-foundation/common_voice_13_0
    metrics:
    - name: Wer
      type: wer
      value: 33.51724137931035
---

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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.
It achieves the following results on the evaluation set:
- Loss: 0.5371
- Wer Ortho: 50.5634
- Wer: 33.5172
  
And the following results on the TORGO + UAS training set:
- Acc: 0.30
- Wer: 80.63
  
## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## 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

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:|
| 3.4478        | 0.35  | 50   | 3.6845          | 67.3239   | 50.4828 |
| 2.3364        | 0.7   | 100  | 2.4193          | 60.5634   | 44.0    |
| 0.2024        | 1.05  | 150  | 0.7172          | 56.4789   | 36.6897 |
| 0.3609        | 1.39  | 200  | 0.5792          | 54.9296   | 36.8276 |
| 0.2227        | 1.74  | 250  | 0.5763          | 53.9437   | 35.4483 |
| 0.0752        | 2.09  | 300  | 0.5516          | 53.6620   | 34.8966 |
| 0.0249        | 2.44  | 350  | 0.5511          | 46.7606   | 29.5172 |
| 0.17          | 2.79  | 400  | 0.5289          | 50.4225   | 31.8621 |
| 0.0736        | 3.14  | 450  | 0.5618          | 51.5493   | 32.5517 |
| 0.0375        | 3.48  | 500  | 0.5371          | 50.5634   | 33.5172 |


### Framework versions

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