---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice_14_0
metrics:
- wer
base_model: facebook/wav2vec2-xls-r-300m
model-index:
- name: XLS-R-LUGANDA-ASR-CV14
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: common_voice_14_0
      type: common_voice_14_0
      config: lg
      split: test
      args: lg
    metrics:
    - type: wer
      value: 0.2406197895094572
      name: Wer
---

<!-- 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-LUGANDA-ASR-CV14

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_14_0 dataset.
It achieves the following results on the evaluation set:
- Loss: inf
- Wer: 0.2406
- Cer: 0.0537

## 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: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- 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: 500
- training_steps: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    | Cer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|
| 4.24          | 0.18  | 400   | inf             | 0.8354 | 0.2170 |
| 0.6124        | 0.36  | 800   | inf             | 0.5690 | 0.1360 |
| 0.4411        | 0.54  | 1200  | inf             | 0.4746 | 0.1120 |
| 0.3839        | 0.72  | 1600  | inf             | 0.4409 | 0.1050 |
| 0.3504        | 0.9   | 2000  | inf             | 0.3955 | 0.0943 |
| 0.3214        | 1.08  | 2400  | inf             | 0.3678 | 0.0854 |
| 0.2879        | 1.26  | 2800  | inf             | 0.3614 | 0.0836 |
| 0.284         | 1.45  | 3200  | inf             | 0.3411 | 0.0789 |
| 0.2683        | 1.63  | 3600  | inf             | 0.3362 | 0.0767 |
| 0.2572        | 1.81  | 4000  | inf             | 0.3241 | 0.0740 |
| 0.2532        | 1.99  | 4400  | inf             | 0.3117 | 0.0719 |
| 0.2228        | 2.17  | 4800  | inf             | 0.2977 | 0.0677 |
| 0.2143        | 2.35  | 5200  | inf             | 0.2969 | 0.0676 |
| 0.211         | 2.53  | 5600  | inf             | 0.2918 | 0.0665 |
| 0.2066        | 2.71  | 6000  | inf             | 0.2848 | 0.0647 |
| 0.2026        | 2.89  | 6400  | inf             | 0.2804 | 0.0637 |
| 0.1898        | 3.07  | 6800  | inf             | 0.2744 | 0.0627 |
| 0.1747        | 3.25  | 7200  | inf             | 0.2668 | 0.0603 |
| 0.1667        | 3.43  | 7600  | inf             | 0.2631 | 0.0597 |
| 0.1639        | 3.61  | 8000  | inf             | 0.2558 | 0.0580 |
| 0.1601        | 3.79  | 8400  | inf             | 0.2519 | 0.0567 |
| 0.1546        | 3.98  | 8800  | inf             | 0.2487 | 0.0554 |
| 0.1395        | 4.16  | 9200  | inf             | 0.2449 | 0.0551 |
| 0.1364        | 4.34  | 9600  | inf             | 0.2425 | 0.0542 |
| 0.1341        | 4.52  | 10000 | inf             | 0.2406 | 0.0537 |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.2.1
- Datasets 2.17.0
- Tokenizers 0.15.2