---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
datasets:
- common_voice_17_0
metrics:
- wer
model-index:
- name: result_data-1
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_17_0
      type: common_voice_17_0
      config: uk
      split: test
      args: uk
    metrics:
    - name: Wer
      type: wer
      value: 0.36512878573450325
---

<!-- 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. -->

# result_data-1

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice_17_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2220
- Wer: 0.3651
- Cer: 0.1691

## 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: 6.532628754904162e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 32
- total_eval_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 206
- num_epochs: 7.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:------:|:----:|:---------------:|:------:|:------:|
| 0.6324        | 0.9099 | 1000 | 0.5004          | 0.6083 | 0.2381 |
| 0.3497        | 1.8198 | 2000 | 0.3087          | 0.4650 | 0.1965 |
| 0.2642        | 2.7298 | 3000 | 0.2636          | 0.4249 | 0.1841 |
| 0.2328        | 3.6397 | 4000 | 0.2431          | 0.3960 | 0.1789 |
| 0.1933        | 4.5496 | 5000 | 0.2289          | 0.3773 | 0.1732 |
| 0.1783        | 5.4595 | 6000 | 0.2300          | 0.3728 | 0.1711 |
| 0.1617        | 6.3694 | 7000 | 0.2233          | 0.3637 | 0.1700 |


### Framework versions

- Transformers 4.49.0
- Pytorch 2.6.0+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0