---
license: apache-2.0
tags:
- automatic-speech-recognition
- google/fleurs
- generated_from_trainer
datasets:
- fleurs
metrics:
- wer
model-index:
- name: facebook/wav2vec2-xls-r-1b
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: GOOGLE/FLEURS - PS_AF
      type: fleurs
      config: ps_af
      split: test
      args: 'Config: ps_af, Training split: train+validation, Eval split: test'
    metrics:
    - name: Wer
      type: wer
      value: 0.9294849931787176
---

<!-- 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. -->

# facebook/wav2vec2-xls-r-1b

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the GOOGLE/FLEURS - PS_AF dataset.
It achieves the following results on the evaluation set:
- Loss: 4.1921
- Wer: 0.9295
- Cer: 0.9608

## 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: 7.5e-05
- 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: 1000
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Cer    | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:------:|:---------------:|:------:|
| 19.9558       | 1.27  | 100  | 3.2660 | 20.9197         | 1.0    |
| 19.7186       | 2.53  | 200  | 1.1692 | 19.2447         | 1.0    |
| 15.203        | 3.8   | 300  | 0.9687 | 15.0053         | 0.9998 |
| 6.4303        | 5.06  | 400  | 0.9911 | 6.5437          | 0.9632 |
| 4.5712        | 6.33  | 500  | 0.9546 | 4.9040          | 0.9323 |
| 3.3986        | 12.66 | 1000 | 4.1921 | 0.9295          | 0.9608 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2