---
tags:
- generated_from_trainer
datasets:
- google/fleurs
metrics:
- wer
model-index:
- name: xls-r-fleurs_zu-run3
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: audiofolder
      type: audiofolder
      config: default
      split: validation
      args: default
    metrics:
    - name: Wer
      type: wer
      value: 0.5777717243257968
---

<!-- 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-fleurs_zu-run3

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the FLEURS (zu) dataset.
It achieves the following results:
- Wer (Validation): 57.19%
- Wer (Test): 57.27%

### 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)   |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.1019        | 0.28  | 50   | 0.5804          | 0.5710 |
| 0.1136        | 0.57  | 100  | 0.5462          | 0.5745 |
| 0.1122        | 0.85  | 150  | 0.5401          | 0.5650 |
| 0.097         | 1.14  | 200  | 0.5680          | 0.5598 |
| 0.0938        | 1.42  | 250  | 0.5763          | 0.5603 |
| 0.1004        | 1.7   | 300  | 0.5803          | 0.5778 |


### Framework versions

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