---
language:
- ug
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_7_0
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: uyghur
  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. -->

# uyghur

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_7_0 - UG dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2266
- Wer: 0.3655

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 3.6863        | 2.73  | 500  | 3.5362          | 1.0    |
| 3.1409        | 5.46  | 1000 | 3.1328          | 1.0    |
| 1.8979        | 8.2   | 1500 | 0.9715          | 0.8864 |
| 1.4859        | 10.93 | 2000 | 0.5234          | 0.7063 |
| 1.3388        | 13.66 | 2500 | 0.4094          | 0.6203 |
| 1.2531        | 16.39 | 3000 | 0.3596          | 0.5185 |
| 1.1992        | 19.13 | 3500 | 0.3221          | 0.4854 |
| 1.1589        | 21.86 | 4000 | 0.3040          | 0.4610 |
| 1.1345        | 24.59 | 4500 | 0.2907          | 0.4450 |
| 1.086         | 27.32 | 5000 | 0.2744          | 0.4299 |
| 1.0697        | 30.05 | 5500 | 0.2617          | 0.4148 |
| 1.0518        | 32.79 | 6000 | 0.2563          | 0.4033 |
| 1.0101        | 35.52 | 6500 | 0.2480          | 0.3934 |
| 1.0013        | 38.25 | 7000 | 0.2412          | 0.3855 |
| 0.9845        | 40.98 | 7500 | 0.2397          | 0.3771 |
| 0.9739        | 43.72 | 8000 | 0.2303          | 0.3726 |
| 0.9636        | 46.45 | 8500 | 0.2285          | 0.3687 |
| 0.9466        | 49.18 | 9000 | 0.2261          | 0.3648 |


### Framework versions

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