---
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: 0.7612841022711041
---

<!-- 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: 1.1618
- Wer: 0.7613

## 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: 0.0001
- 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 8.7106        | 6.25  | 50   | 4.0034          | 1.0    |
| 3.4036        | 12.5  | 100  | 3.1030          | 1.0    |
| 3.7265        | 18.75 | 150  | 3.0466          | 1.0    |
| 3.2292        | 25.0  | 200  | 3.0166          | 1.0    |
| 3.1305        | 31.25 | 250  | 2.9699          | 1.0    |
| 3.0447        | 37.5  | 300  | 2.9144          | 1.0    |
| 2.9037        | 43.75 | 350  | 2.2919          | 0.9998 |
| 2.1115        | 50.0  | 400  | 1.3995          | 0.9429 |
| 1.3456        | 56.25 | 450  | 1.1093          | 0.8435 |
| 1.3206        | 62.5  | 500  | 1.1573          | 0.8112 |
| 1.0078        | 68.75 | 550  | 1.1746          | 0.7757 |
| 1.0674        | 75.0  | 600  | 1.1618          | 0.7613 |


### Framework versions

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