---
base_model: facebook/wav2vec2-xls-r-300m
datasets:
- common_voice_13_0
license: apache-2.0
metrics:
- wer
tags:
- generated_from_trainer
model-index:
- name: XLS-R-demo-google-colab-Ezra_William_Prod_1
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: common_voice_13_0
      type: common_voice_13_0
      config: id
      split: validation
      args: id
    metrics:
    - type: wer
      value: 0.5410194506445588
      name: Wer
---

<!-- 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-demo-google-colab-Ezra_William_Prod_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_13_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6266
- Wer: 0.5410

## 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: 0.0001
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 12
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 4.5357        | 1.0   | 121  | 2.9681          | 1.0    |
| 2.9324        | 2.0   | 242  | 2.8618          | 1.0    |
| 2.8708        | 3.0   | 363  | 2.4604          | 1.0    |
| 2.4605        | 4.0   | 484  | 0.8385          | 0.7171 |
| 0.5712        | 5.0   | 605  | 0.6917          | 0.6913 |
| 0.4235        | 6.0   | 726  | 0.6216          | 0.6121 |
| 0.3508        | 7.0   | 847  | 0.5942          | 0.5765 |
| 0.2953        | 8.0   | 968  | 0.6049          | 0.5710 |
| 0.2543        | 9.0   | 1089 | 0.6319          | 0.5605 |
| 0.1985        | 10.0  | 1210 | 0.6327          | 0.5544 |
| 0.1819        | 11.0  | 1331 | 0.6229          | 0.5412 |
| 0.1745        | 12.0  | 1452 | 0.6266          | 0.5410 |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1