---
license: apache-2.0
tags:
- 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 common_voice dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2163
- Wer: 0.3241

## 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: 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: 100.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 3.2914        | 4.85  | 500   | 3.2283          | 1.0    |
| 3.0068        | 9.71  | 1000  | 2.7939          | 0.9980 |
| 1.4306        | 14.56 | 1500  | 0.4857          | 0.6314 |
| 1.2831        | 19.42 | 2000  | 0.3679          | 0.6066 |
| 1.2065        | 24.27 | 2500  | 0.3303          | 0.5560 |
| 1.1449        | 29.13 | 3000  | 0.3008          | 0.4690 |
| 1.0926        | 33.98 | 3500  | 0.2817          | 0.4619 |
| 1.0635        | 38.83 | 4000  | 0.2665          | 0.4391 |
| 1.029         | 43.69 | 4500  | 0.2616          | 0.4175 |
| 1.0064        | 48.54 | 5000  | 0.2468          | 0.4051 |
| 0.9659        | 53.4  | 5500  | 0.2394          | 0.3860 |
| 0.9254        | 58.25 | 6000  | 0.2373          | 0.3689 |
| 0.9209        | 63.11 | 6500  | 0.2347          | 0.3670 |
| 0.889         | 67.96 | 7000  | 0.2291          | 0.3687 |
| 0.8859        | 72.82 | 7500  | 0.2272          | 0.3616 |
| 0.8441        | 77.67 | 8000  | 0.2232          | 0.3538 |
| 0.8284        | 82.52 | 8500  | 0.2224          | 0.3382 |
| 0.8142        | 87.38 | 9000  | 0.2193          | 0.3310 |
| 0.8012        | 92.23 | 9500  | 0.2168          | 0.3276 |
| 0.7781        | 97.09 | 10000 | 0.2163          | 0.3241 |


### Framework versions

- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu102
- Datasets 1.18.3
- Tokenizers 0.11.0