---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: xls-r-asr_af-run5
  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-run5

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):
- Wer (Test):

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0003
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- 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: 500
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer (Train)    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 11.7451       | 0.58  | 50   | 7.2710          | 1.0    |
| 4.7931        | 1.17  | 100  | 4.0381          | 1.0    |
| 3.4944        | 1.75  | 150  | 3.1782          | 1.0    |
| 3.06          | 2.34  | 200  | 2.9951          | 1.0    |
| 3.0031        | 2.92  | 250  | 2.9964          | 1.0    |
| 2.9814        | 3.51  | 300  | 2.9652          | 1.0    |
| 2.9524        | 4.09  | 350  | 2.9419          | 0.9998 |
| 2.9014        | 4.68  | 400  | 2.8213          | 1.0    |
| 2.2569        | 5.26  | 450  | 1.6105          | 0.9433 |
| 1.3008        | 5.85  | 500  | 1.0090          | 0.8021 |
| 0.8965        | 6.43  | 550  | 0.7727          | 0.6551 |
| 0.7134        | 7.02  | 600  | 0.6579          | 0.6102 |
| 0.5275        | 7.6   | 650  | 0.5956          | 0.6005 |
| 0.4413        | 8.19  | 700  | 0.5558          | 0.5079 |
| 0.3582        | 8.77  | 750  | 0.5719          | 0.5459 |
| 0.296         | 9.36  | 800  | 0.5389          | 0.4822 |
| 0.2557        | 9.94  | 850  | 0.4608          | 0.4541 |
| 0.2051        | 10.53 | 900  | 0.4822          | 0.4290 |
| 0.1911        | 11.11 | 950  | 0.5035          | 0.4209 |
| 0.1635        | 11.7  | 1000 | 0.5319          | 0.4263 |
| 0.1582        | 12.28 | 1050 | 0.5075          | 0.4124 |
| 0.1387        | 12.87 | 1100 | 0.4759          | 0.4055 |
| 0.1251        | 13.45 | 1150 | 0.4925          | 0.3970 |
| 0.1164        | 14.04 | 1200 | 0.4933          | 0.3998 |
| 0.1052        | 14.62 | 1250 | 0.4587          | 0.3995 |
| 0.1023        | 15.2  | 1300 | 0.4863          | 0.3950 |
| 0.0918        | 15.79 | 1350 | 0.5114          | 0.3858 |
| 0.09          | 16.37 | 1400 | 0.5444          | 0.3940 |
| 0.086         | 16.96 | 1450 | 0.5071          | 0.3806 |
| 0.0798        | 17.54 | 1500 | 0.4914          | 0.3809 |
| 0.0728        | 18.13 | 1550 | 0.5425          | 0.3807 |
| 0.0678        | 18.71 | 1600 | 0.5221          | 0.3731 |
| 0.0667        | 19.3  | 1650 | 0.5239          | 0.3726 |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3