---
language:
- ug
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_11_0
- generated_from_trainer
datasets:
- common_voice_11_0
metrics:
- wer
model-index:
- name: xls-r-uyghur-cv11
  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-cv11

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_11_0 - UG dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2191
- Wer: 0.3257

## 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: 0.0001
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2000
- num_epochs: 100.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 3.3958        | 4.36  | 500   | 3.3137          | 1.0    |
| 3.032         | 8.71  | 1000  | 2.8586          | 0.9993 |
| 1.3977        | 13.07 | 1500  | 0.4786          | 0.6375 |
| 1.2751        | 17.43 | 2000  | 0.3816          | 0.5393 |
| 1.2113        | 21.79 | 2500  | 0.3451          | 0.5099 |
| 1.156         | 26.14 | 3000  | 0.3245          | 0.4919 |
| 1.1226        | 30.5  | 3500  | 0.2992          | 0.4441 |
| 1.0913        | 34.86 | 4000  | 0.2831          | 0.4315 |
| 1.0615        | 39.22 | 4500  | 0.2808          | 0.4340 |
| 1.0455        | 43.57 | 5000  | 0.2713          | 0.4088 |
| 1.0228        | 47.93 | 5500  | 0.2622          | 0.3960 |
| 0.9936        | 52.29 | 6000  | 0.2525          | 0.3796 |
| 0.968         | 56.64 | 6500  | 0.2506          | 0.3798 |
| 0.9704        | 61.0  | 7000  | 0.2481          | 0.3735 |
| 0.9552        | 65.36 | 7500  | 0.2394          | 0.3643 |
| 0.9417        | 69.72 | 8000  | 0.2350          | 0.3537 |
| 0.9215        | 74.07 | 8500  | 0.2326          | 0.3507 |
| 0.9097        | 78.43 | 9000  | 0.2277          | 0.3487 |
| 0.9003        | 82.79 | 9500  | 0.2230          | 0.3362 |
| 0.8857        | 87.15 | 10000 | 0.2246          | 0.3362 |
| 0.882         | 91.5  | 10500 | 0.2236          | 0.3315 |
| 0.8719        | 95.86 | 11000 | 0.2203          | 0.3271 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0