---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: xls-r-asr_af-run2
  results: []
datasets:
- lucas-meyer/asr_af
---

<!-- 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. -->

# xls-r-asr_af-run2

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the asr_af dataset.
It achieves the following results:
- Wer (Validation): 42.47%
- Wer (Test): 43.42%

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0003
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 3
- total_train_batch_size: 12
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer (Train)    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 8.6534        | 0.44  | 100  | 4.1962          | 1.0    |
| 3.3291        | 0.88  | 200  | 2.9968          | 1.0    |
| 2.9771        | 1.32  | 300  | 2.9616          | 1.0    |
| 2.6613        | 1.76  | 400  | 1.7252          | 0.9456 |
| 1.2954        | 2.2   | 500  | 1.0669          | 0.8175 |
| 0.8676        | 2.64  | 600  | 0.7491          | 0.6426 |
| 0.6715        | 3.08  | 700  | 0.5918          | 0.5330 |
| 0.4916        | 3.52  | 800  | 0.5411          | 0.4762 |
| 0.4443        | 3.96  | 900  | 0.5167          | 0.4767 |
| 0.3304        | 4.41  | 1000 | 0.5264          | 0.4533 |
| 0.3162        | 4.85  | 1100 | 0.5299          | 0.4675 |
| 0.2931        | 5.29  | 1200 | 0.4696          | 0.4192 |
| 0.2472        | 5.73  | 1300 | 0.4630          | 0.4252 |
| 0.2312        | 6.17  | 1400 | 0.4824          | 0.4164 |
| 0.2007        | 6.61  | 1500 | 0.4637          | 0.4035 |
| 0.2036        | 7.05  | 1600 | 0.4802          | 0.3983 |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3