---
license: mit
base_model: distil-whisper/distil-medium.en
tags:
- generated_from_trainer
datasets:
- dysarthria
metrics:
- accuracy
model-index:
- name: distil-medium.en-dysarthia-non-dysathira-detection-fm
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: Dysarthria
      type: dysarthria
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.975
---

<!-- 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. -->

# distil-medium.en-dysarthia-non-dysathira-detection-fm

This model is a fine-tuned version of [distil-whisper/distil-medium.en](https://huggingface.co/distil-whisper/distil-medium.en) on the Dysarthria dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1593
- Accuracy: 0.975

## 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: 5e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.875         | 1.0   | 160  | 0.4243          | 0.8875   |
| 0.0264        | 2.0   | 320  | 1.2160          | 0.8125   |
| 0.0115        | 3.0   | 480  | 0.2111          | 0.95     |
| 0.3632        | 4.0   | 640  | 0.1856          | 0.975    |
| 0.0933        | 5.0   | 800  | 0.7655          | 0.9      |
| 0.0003        | 6.0   | 960  | 0.6221          | 0.9      |
| 0.0001        | 7.0   | 1120 | 0.1163          | 0.9875   |
| 0.0001        | 8.0   | 1280 | 0.3188          | 0.95     |
| 0.0001        | 9.0   | 1440 | 0.1662          | 0.975    |
| 0.0001        | 10.0  | 1600 | 0.1593          | 0.975    |


### Framework versions

- Transformers 4.41.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1