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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: seq-xls-r-fleurs_nl-run2-asr_af-run1
  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-run1

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): 41.40%
 - Wer (Test): 42.51%

### 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) |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 11.461        | 0.22  | 50   | 5.5845          | 1.0    |
| 3.9953        | 0.44  | 100  | 3.3273          | 1.0    |
| 3.1257        | 0.66  | 150  | 3.0364          | 1.0    |
| 2.9891        | 0.88  | 200  | 2.9621          | 0.9998 |
| 2.638         | 1.32  | 250  | 2.0895          | 0.9998 |
| 1.6636        | 1.54  | 300  | 1.2631          | 0.8508 |
| 1.0747        | 1.76  | 350  | 0.8712          | 0.6416 |
| 0.8364        | 1.98  | 400  | 0.7328          | 0.5799 |
| 0.6266        | 2.2   | 450  | 0.6809          | 0.5547 |
| 0.5862        | 2.42  | 500  | 0.6168          | 0.5084 |
| 0.5767        | 2.64  | 550  | 0.5535          | 0.4873 |
| 0.4972        | 2.86  | 600  | 0.5432          | 0.4930 |
| 0.4721        | 3.08  | 650  | 0.4796          | 0.4409 |
| 0.3629        | 3.3   | 700  | 0.4508          | 0.4201 |
| 0.3429        | 3.52  | 750  | 0.4479          | 0.4144 |
| 0.3441        | 3.74  | 800  | 0.4721          | 0.4133 |
| 0.3349        | 3.96  | 850  | 0.4564          | 0.4178 |
| 0.27          | 4.19  | 900  | 0.4629          | 0.3955 |
| 0.2453        | 4.42  | 950  | 0.4569          | 0.3723 |

### Framework versions

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