---
language:
- ug
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_8_0
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: xls-r-uyghur-cv8
  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. -->

# xls-r-uyghur-cv8

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - UG dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2430
- Wer: 0.3804

## 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: 7.5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2000
- num_epochs: 50.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 3.6871        | 2.66  | 500  | 3.5374          | 1.0    |
| 3.1501        | 5.32  | 1000 | 3.1278          | 1.0    |
| 1.5843        | 7.97  | 1500 | 0.6358          | 0.6914 |
| 1.3378        | 10.64 | 2000 | 0.4422          | 0.5925 |
| 1.2595        | 13.3  | 2500 | 0.3921          | 0.5512 |
| 1.1643        | 15.95 | 3000 | 0.3507          | 0.5149 |
| 1.1352        | 18.61 | 3500 | 0.3351          | 0.5019 |
| 1.1113        | 21.28 | 4000 | 0.3153          | 0.4845 |
| 1.0914        | 23.93 | 4500 | 0.3050          | 0.4594 |
| 1.0468        | 26.59 | 5000 | 0.2890          | 0.4470 |
| 1.0473        | 29.25 | 5500 | 0.2755          | 0.4331 |
| 1.0065        | 31.91 | 6000 | 0.2718          | 0.4264 |
| 0.9794        | 34.57 | 6500 | 0.2646          | 0.4193 |
| 0.9849        | 37.23 | 7000 | 0.2610          | 0.4058 |
| 0.9496        | 39.89 | 7500 | 0.2522          | 0.3985 |
| 0.9367        | 42.55 | 8000 | 0.2514          | 0.3947 |
| 0.9295        | 45.21 | 8500 | 0.2458          | 0.3883 |
| 0.9187        | 47.87 | 9000 | 0.2439          | 0.3833 |


### Framework versions

- Transformers 4.16.0.dev0
- Pytorch 1.10.1+cu102
- Datasets 1.18.2.dev0
- Tokenizers 0.11.0