---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: xls-r-asr_xh-run6
  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. -->

# xls-r-asr_xh-run6

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the asr_xh dataset.
It achieves the following results:
- Wer (Validation): 53.06%
- Wer (Test): 53.88%

### 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)    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 10.217        | 0.64  | 100  | 4.3372          | 1.0    |
| 3.5916        | 1.27  | 200  | 3.0758          | 1.0    |
| 3.04          | 1.91  | 300  | 2.8524          | 1.0    |
| 1.8074        | 2.55  | 400  | 0.8240          | 0.8711 |
| 0.7939        | 3.18  | 500  | 0.6766          | 0.8073 |
| 0.6324        | 3.82  | 600  | 0.5092          | 0.6501 |
| 0.4725        | 4.46  | 700  | 0.5041          | 0.6139 |
| 0.4319        | 5.1   | 800  | 0.4249          | 0.5892 |
| 0.3264        | 5.73  | 900  | 0.4713          | 0.5905 |
| 0.3122        | 6.37  | 1000 | 0.4220          | 0.5513 |
| 0.2631        | 7.01  | 1100 | 0.4722          | 0.5659 |
| 0.2203        | 7.64  | 1200 | 0.4176          | 0.5306 |
| 0.2113        | 8.28  | 1300 | 0.4374          | 0.5468 |
| 0.1885        | 8.92  | 1400 | 0.4484          | 0.5021 |


### Framework versions

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