transformers pytorch tensorboard wav2vec2 automatic-speech-recognition generated_from_trainer dataset:lucas-meyer/asr_af license:apache-2.0 endpoints_compatible region:us
---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: seq-xls-r-fleurs_nl-run2-asr_af-run2
  results: []
datasets:
- lucas-meyer/asr_af
---

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

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): 38.75%
- Wer (Test): 38.66%

### 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) |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 7.6065        | 0.44  | 100  | 3.3086          | 1.0    |
| 3.055         | 0.88  | 200  | 2.9676          | 0.9998 |
| 2.7713        | 1.32  | 300  | 1.9810          | 0.9998 |
| 1.3251        | 1.76  | 400  | 0.8096          | 0.6136 |
| 0.7431        | 2.2   | 500  | 0.6821          | 0.5622 |
| 0.5789        | 2.64  | 600  | 0.5596          | 0.5133 |
| 0.4866        | 3.08  | 700  | 0.4707          | 0.4381 |
| 0.3558        | 3.52  | 800  | 0.4653          | 0.4353 |
| 0.3362        | 3.96  | 900  | 0.4878          | 0.4235 |
| 0.2631        | 4.41  | 1000 | 0.4621          | 0.3907 |
| 0.2667        | 4.85  | 1100 | 0.4746          | 0.3841 |
| 0.2464        | 5.29  | 1200 | 0.4383          | 0.3780 |
| 0.205         | 5.73  | 1300 | 0.4207          | 0.3877 |
| 0.1939        | 6.17  | 1400 | 0.4490          | 0.3746 |
| 0.1644        | 6.61  | 1500 | 0.4325          | 0.3549 |
| 0.1782        | 7.05  | 1600 | 0.4699          | 0.3791 |


### Framework versions

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