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---
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
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