---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: seq-xls-r-fleurs_nl-run2-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. -->

# seq-xls-r-fleurs_nl-run2-asr_af-run5

This model is a fine-tuned version of [lucas-meyer/xls-r-fleurs_nl-run2](https://huggingface.co/lucas-meyer/xls-r-fleurs_nl-run2) on the asr_af dataset.
It achieves the following results:
- Wer (Validation): 37.23%
- Wer (Test): 37.78%

### 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: 16
- 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)    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 11.2739       | 0.29  | 50   | 5.2927          | 1.0    |
| 3.8398        | 0.59  | 100  | 3.3122          | 1.0    |
| 3.1152        | 0.88  | 150  | 3.0188          | 1.0    |
| 2.9857        | 1.17  | 200  | 2.9748          | 0.9998 |
| 2.8793        | 1.47  | 250  | 2.7253          | 1.0    |
| 2.0828        | 1.76  | 300  | 1.5219          | 0.9291 |
| 1.1713        | 2.05  | 350  | 0.8089          | 0.6017 |
| 0.74          | 2.35  | 400  | 0.6447          | 0.5613 |
| 0.6223        | 2.64  | 450  | 0.5806          | 0.4899 |
| 0.5661        | 2.93  | 500  | 0.5890          | 0.4928 |
| 0.4624        | 3.23  | 550  | 0.5796          | 0.4767 |
| 0.4107        | 3.52  | 600  | 0.5077          | 0.4624 |
| 0.3755        | 3.81  | 650  | 0.4489          | 0.4109 |
| 0.3255        | 4.11  | 700  | 0.4474          | 0.3887 |
| 0.2728        | 4.4   | 750  | 0.4477          | 0.3958 |
| 0.2756        | 4.69  | 800  | 0.4477          | 0.3841 |
| 0.282         | 4.99  | 850  | 0.4243          | 0.3914 |
| 0.2362        | 5.28  | 900  | 0.4756          | 0.4081 |
| 0.2262        | 5.57  | 950  | 0.4554          | 0.3824 |
| 0.2315        | 5.87  | 1000 | 0.3963          | 0.3721 |
| 0.2016        | 6.16  | 1050 | 0.4290          | 0.3734 |
| 0.1772        | 6.45  | 1100 | 0.4419          | 0.3649 |
| 0.1835        | 6.74  | 1150 | 0.4339          | 0.3560 |


### Framework versions

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