---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
datasets:
- fleurs
metrics:
- wer
model-index:
- name: wav2vec2-xls-r-Wolof-5-hours-Google-Fleurs-dataset
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: fleurs
      type: fleurs
      config: wo_sn
      split: None
      args: wo_sn
    metrics:
    - name: Wer
      type: wer
      value: 0.5271843562789646
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/asr-africa-research-team/ASR%20Africa/runs/his8zfb9)
# wav2vec2-xls-r-Wolof-5-hours-Google-Fleurs-dataset

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the fleurs dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2559
- Wer: 0.5272
- Cer: 0.1866

## 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_ratio: 0.1
- num_epochs: 50

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:-------:|:----:|:---------------:|:------:|:------:|
| 4.7038        | 9.7561  | 400  | 3.0098          | 1.0    | 1.0    |
| 1.508         | 19.5122 | 800  | 0.9104          | 0.5966 | 0.2133 |
| 0.3931        | 29.2683 | 1200 | 1.0558          | 0.5637 | 0.2012 |
| 0.197         | 39.0244 | 1600 | 1.1686          | 0.5404 | 0.1918 |
| 0.1351        | 48.7805 | 2000 | 1.2559          | 0.5272 | 0.1866 |


### Framework versions

- Transformers 4.44.1
- Pytorch 2.1.0+cu118
- Datasets 2.17.0
- Tokenizers 0.19.1