---
language:
- uz
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_8_0
- generated_from_trainer
datasets:
- common_voice_8_0
metrics:
- wer
model-index:
- name: xls-r-uzbek-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-uzbek-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 - UZ dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2924
- Wer: 0.3780
- Cer: 0.0760

## 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: 3e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- 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: 10.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Wer    | Cer    |
|:-------------:|:------:|:-----:|:---------------:|:------:|:------:|
| 3.1444        | 0.4055 | 500   | 3.1200          | 1.0    | 1.0    |
| 2.9488        | 0.8110 | 1000  | 2.9562          | 1.0    | 0.9807 |
| 1.4553        | 1.2165 | 1500  | 0.7868          | 0.7034 | 0.1644 |
| 1.1495        | 1.6221 | 2000  | 0.5598          | 0.6076 | 0.1337 |
| 1.041         | 2.0276 | 2500  | 0.4650          | 0.5537 | 0.1174 |
| 0.9524        | 2.4331 | 3000  | 0.4204          | 0.5098 | 0.1061 |
| 0.902         | 2.8386 | 3500  | 0.3919          | 0.4984 | 0.1026 |
| 0.8505        | 3.2441 | 4000  | 0.3688          | 0.4678 | 0.0965 |
| 0.8353        | 3.6496 | 4500  | 0.3491          | 0.4488 | 0.0915 |
| 0.8015        | 4.0552 | 5000  | 0.3410          | 0.4356 | 0.0896 |
| 0.7771        | 4.4607 | 5500  | 0.3367          | 0.4330 | 0.0883 |
| 0.7894        | 4.8662 | 6000  | 0.3274          | 0.4201 | 0.0858 |
| 0.7624        | 5.2717 | 6500  | 0.3266          | 0.4115 | 0.0835 |
| 0.7522        | 5.6772 | 7000  | 0.3172          | 0.4072 | 0.0825 |
| 0.7545        | 6.0827 | 7500  | 0.3096          | 0.4034 | 0.0817 |
| 0.7412        | 6.4882 | 8000  | 0.3062          | 0.4014 | 0.0810 |
| 0.7405        | 6.8938 | 8500  | 0.3057          | 0.3933 | 0.0796 |
| 0.703         | 7.2993 | 9000  | 0.2966          | 0.3894 | 0.0784 |
| 0.7091        | 7.7048 | 9500  | 0.3000          | 0.3895 | 0.0784 |
| 0.7117        | 8.1103 | 10000 | 0.2988          | 0.3881 | 0.0781 |
| 0.6871        | 8.5158 | 10500 | 0.2939          | 0.3832 | 0.0771 |
| 0.6942        | 8.9213 | 11000 | 0.2950          | 0.3816 | 0.0766 |
| 0.6919        | 9.3268 | 11500 | 0.2910          | 0.3781 | 0.0760 |
| 0.6756        | 9.7324 | 12000 | 0.2927          | 0.3785 | 0.0760 |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.3.0+cu118
- Datasets 2.19.1
- Tokenizers 0.19.1