---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice_8_0
metrics:
- wer
model-index:
- name: wav2vec2-large-xls-r-1b-frisian-cv-8-10m
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_8_0
      type: common_voice_8_0
      config: fy-NL
      split: validation
      args: fy-NL
    metrics:
    - name: Wer
      type: wer
      value: 0.5262462505356378
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_8_0
      type: common_voice_8_0
      config: fy-NL
      split: test
      args: fy-NL
    metrics:
    - name: Wer
      type: wer
      value: 0.6225249313484608
---

<!-- 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. -->

# wav2vec2-large-xls-r-1b-frisian-cv-8-10m

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_8_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9269
- Wer: 0.5262

And on the test set:
- Wer: 0.6225

## 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: 7e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 80
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 9.2929        | 6.25  | 50   | 3.0514          | 1.0    |
| 3.315         | 12.5  | 100  | 3.2255          | 1.0    |
| 3.1506        | 18.75 | 150  | 2.9924          | 1.0    |
| 2.9773        | 25.0  | 200  | 2.2199          | 1.0    |
| 2.1616        | 31.25 | 250  | 1.1423          | 0.8603 |
| 1.6887        | 37.5  | 300  | 0.9730          | 0.7020 |
| 1.1178        | 43.75 | 350  | 0.8971          | 0.6323 |
| 0.9512        | 50.0  | 400  | 0.9040          | 0.5960 |
| 0.7696        | 56.25 | 450  | 0.9232          | 0.5713 |
| 0.7348        | 62.5  | 500  | 0.9203          | 0.5412 |
| 0.9312        | 68.75 | 550  | 0.9673          | 0.5376 |
| 0.6519        | 75.0  | 600  | 0.9269          | 0.5262 |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu117
- Datasets 2.11.0
- Tokenizers 0.13.3