---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- fleurs
metrics:
- wer
model-index:
- name: xlsr-53-ur
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: fleurs
      type: fleurs
      config: ur_pk
      split: test
      args: ur_pk
    metrics:
    - name: Wer
      type: wer
      value: 0.3450557529714496
---

<!-- 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. -->

# xlsr-53-ur

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the fleurs dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6860
- Wer: 0.3451

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0003
- train_batch_size: 6
- eval_batch_size: 6
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 12
- total_eval_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: 15.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 3.0396        | 1.59  | 300  | 3.0179          | 1.0    |
| 0.4976        | 3.17  | 600  | 0.7037          | 0.5447 |
| 0.3062        | 4.76  | 900  | 0.5557          | 0.4036 |
| 0.2287        | 6.35  | 1200 | 0.5620          | 0.3935 |
| 0.2504        | 7.94  | 1500 | 0.5907          | 0.3677 |
| 0.0633        | 9.52  | 1800 | 0.6239          | 0.3773 |
| 0.0456        | 11.11 | 2100 | 0.6748          | 0.3604 |
| 0.0774        | 12.7  | 2400 | 0.6747          | 0.3552 |
| 0.058         | 14.29 | 2700 | 0.6860          | 0.3451 |


### Framework versions

- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2