---
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-large-xls-r-300m-dysarthria
  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

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0615
- Wer: 0.1764

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 16.998        | 2.17  | 400  | 3.4205          | 1.0    |
| 3.6507        | 4.34  | 800  | 3.2819          | 1.0    |
| 3.2148        | 6.5   | 1200 | 3.0239          | 1.0    |
| 2.8464        | 8.67  | 1600 | 2.5810          | 1.0    |
| 2.3923        | 10.84 | 2000 | 2.2368          | 1.0    |
| 1.9358        | 13.01 | 2400 | 1.7072          | 1.0    |
| 1.5043        | 15.18 | 2800 | 1.3435          | 1.0    |
| 1.1169        | 17.34 | 3200 | 0.8979          | 0.9701 |
| 0.749         | 19.51 | 3600 | 0.5764          | 0.7490 |
| 0.4855        | 21.68 | 4000 | 0.2876          | 0.4763 |
| 0.2902        | 23.85 | 4400 | 0.1645          | 0.3379 |
| 0.198         | 26.02 | 4800 | 0.0988          | 0.2307 |
| 0.1358        | 28.18 | 5200 | 0.0615          | 0.1764 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1