---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-large-xls-r-1b-frisian-cv-13-elderly-augmented
  results: []
---

<!-- 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-13-elderly-augmented

This model is a fine-tuned version of [greenw0lf/wav2vec2-large-xls-r-1b-frisian](https://huggingface.co/greenw0lf/wav2vec2-large-xls-r-1b-frisian) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2158
- Wer: 0.2709

## 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: 9e-06
- train_batch_size: 32
- 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: 40
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 5.7704        | 2.5   | 50   | 3.5242          | 1.0040 |
| 2.7638        | 5.0   | 100  | 1.8583          | 1.0523 |
| 1.4635        | 7.5   | 150  | 0.5541          | 0.5861 |
| 0.6753        | 10.0  | 200  | 0.2995          | 0.3353 |
| 0.4331        | 12.5  | 250  | 0.2439          | 0.2964 |
| 0.7712        | 15.0  | 300  | 0.2344          | 0.2879 |
| 0.6968        | 17.5  | 350  | 0.2287          | 0.2839 |
| 0.2765        | 20.0  | 400  | 0.2249          | 0.2776 |
| 0.4245        | 22.5  | 450  | 0.2202          | 0.2776 |
| 0.3709        | 25.0  | 500  | 0.2192          | 0.2754 |
| 0.4728        | 27.5  | 550  | 0.2195          | 0.2763 |
| 0.6297        | 30.0  | 600  | 0.2191          | 0.2736 |
| 0.5297        | 32.5  | 650  | 0.2186          | 0.2758 |
| 0.3543        | 35.0  | 700  | 0.2171          | 0.2731 |
| 0.2973        | 37.5  | 750  | 0.2167          | 0.2713 |
| 0.4558        | 40.0  | 800  | 0.2158          | 0.2709 |


### Framework versions

- Transformers 4.27.4
- Pytorch 2.0.0+cu117
- Datasets 2.11.0
- Tokenizers 0.13.2