---
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-1b
tags:
- generated_from_trainer
datasets:
- common_voice_13_0
metrics:
- wer
model-index:
- name: LugandaASRwav20Vec1B
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_13_0
      type: common_voice_13_0
      config: lg
      split: validation
      args: lg
    metrics:
    - name: Wer
      type: wer
      value: 0.23043478260869565
---

<!-- 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. -->

# LugandaASRwav20Vec1B

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the common_voice_13_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1854
- Wer: 0.2304

## 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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 24
- total_train_batch_size: 96
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 4.303         | 0.14  | 100  | 2.1141          | 1.0    |
| 0.7155        | 0.27  | 200  | 0.5656          | 0.6752 |
| 0.4493        | 0.41  | 300  | 0.4402          | 0.5607 |
| 0.3964        | 0.54  | 400  | 0.3918          | 0.5114 |
| 0.3646        | 0.68  | 500  | 0.3601          | 0.4592 |
| 0.3294        | 0.81  | 600  | 0.3381          | 0.4467 |
| 0.3339        | 0.95  | 700  | 0.3340          | 0.4266 |
| 0.2893        | 1.08  | 800  | 0.2913          | 0.3670 |
| 0.2743        | 1.22  | 900  | 0.2854          | 0.3600 |
| 0.262         | 1.36  | 1000 | 0.2666          | 0.3318 |
| 0.2545        | 1.49  | 1100 | 0.2601          | 0.3341 |
| 0.2437        | 1.63  | 1200 | 0.2488          | 0.3152 |
| 0.2235        | 1.76  | 1300 | 0.2416          | 0.3015 |
| 0.2188        | 1.9   | 1400 | 0.2330          | 0.2902 |
| 0.2054        | 2.03  | 1500 | 0.2218          | 0.2750 |
| 0.1743        | 2.17  | 1600 | 0.2153          | 0.2672 |
| 0.1722        | 2.3   | 1700 | 0.2098          | 0.2575 |
| 0.1656        | 2.44  | 1800 | 0.2011          | 0.2538 |
| 0.1608        | 2.58  | 1900 | 0.2000          | 0.2475 |
| 0.1574        | 2.71  | 2000 | 0.1937          | 0.2428 |
| 0.1531        | 2.85  | 2100 | 0.1882          | 0.2347 |
| 0.1451        | 2.98  | 2200 | 0.1854          | 0.2304 |


### Framework versions

- Transformers 4.32.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.0
- Tokenizers 0.13.3