---
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: seq-xls-r-fleurs_zu-run3-asr_xh-run5
  results: []
datasets:
- lucas-meyer/asr_xh
---

<!-- 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_zu-run3-asr_xh-run5

This model is a fine-tuned version of [lucas-meyer/xls-r-fleurs_zu-run3](https://huggingface.co/lucas-meyer/xls-r-fleurs_zu-run3) on the asr_xh dataset.
It achieves the following results:
- Wer (Validation): 55.78%
- Wer (Test): 57.66%

### 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)    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 14.2303       | 0.32  | 50   | 6.1214          | 1.0    |
| 4.1753        | 0.64  | 100  | 3.3769          | 1.0    |
| 3.263         | 0.96  | 150  | 3.0843          | 1.0    |
| 3.0162        | 1.27  | 200  | 2.7783          | 1.0    |
| 1.9813        | 1.59  | 250  | 0.8590          | 0.8218 |
| 0.841         | 1.91  | 300  | 0.5767          | 0.6932 |
| 0.7204        | 2.23  | 350  | 0.5838          | 0.7140 |
| 0.5802        | 2.55  | 400  | 0.5019          | 0.6793 |
| 0.5307        | 2.87  | 450  | 0.4409          | 0.6203 |
| 0.4678        | 3.18  | 500  | 0.4813          | 0.6064 |
| 0.4309        | 3.5   | 550  | 0.5182          | 0.6375 |
| 0.44          | 3.82  | 600  | 0.3939          | 0.5594 |
| 0.3664        | 4.14  | 650  | 0.4210          | 0.5585 |
| 0.3169        | 4.46  | 700  | 0.4745          | 0.5873 |
| 0.3344        | 4.78  | 750  | 0.4249          | 0.5526 |


### Framework versions

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