---
base_model: jmaczan/wav2vec2-large-xls-r-300m-dysarthria
license: apache-2.0
metrics:
- wer
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-large-xls-r-300m-dysarthria-big-dataset
  results: []
---

<!-- 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. -->

# wav2vec2-large-xls-r-300m-dysarthria-big-dataset

This model is a fine-tuned version of [jmaczan/wav2vec2-large-xls-r-300m-dysarthria](https://huggingface.co/jmaczan/wav2vec2-large-xls-r-300m-dysarthria) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0313
- Wer: 0.28

## 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: 0.0003
- train_batch_size: 8
- eval_batch_size: 8
- 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: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer   |
|:-------------:|:-----:|:----:|:---------------:|:-----:|
| 3.1965        | 1.6   | 200  | 1.7709          | 0.88  |
| 1.6135        | 3.2   | 400  | 1.1347          | 0.764 |
| 1.1769        | 4.8   | 600  | 0.9348          | 0.722 |
| 0.8155        | 6.4   | 800  | 0.5330          | 0.576 |
| 0.5961        | 8.0   | 1000 | 0.3927          | 0.504 |
| 0.4436        | 9.6   | 1200 | 0.3171          | 0.488 |
| 0.3581        | 11.2  | 1400 | 0.2877          | 0.512 |
| 0.2931        | 12.8  | 1600 | 0.1590          | 0.354 |
| 0.219         | 14.4  | 1800 | 0.1370          | 0.326 |
| 0.1912        | 16.0  | 2000 | 0.1362          | 0.262 |
| 0.1543        | 17.6  | 2200 | 0.0823          | 0.238 |
| 0.1323        | 19.2  | 2400 | 0.0764          | 0.272 |
| 0.1095        | 20.8  | 2600 | 0.0649          | 0.272 |
| 0.0909        | 22.4  | 2800 | 0.0537          | 0.274 |
| 0.0807        | 24.0  | 3000 | 0.0499          | 0.248 |
| 0.0618        | 25.6  | 3200 | 0.0499          | 0.318 |
| 0.0573        | 27.2  | 3400 | 0.0414          | 0.252 |
| 0.0456        | 28.8  | 3600 | 0.0313          | 0.28  |


### Framework versions

- Transformers 4.43.2
- Pytorch 2.2.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1