---
license: apache-2.0
tags:
- generated_from_trainer
base_model: facebook/wav2vec2-xls-r-300m
datasets:
- common_voice_13_0
metrics:
- wer
model-index:
- name: wav2vec2-xlsr-53-CV-demo-google-colab-Ezra_William_Prod17
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: common_voice_13_0
      type: common_voice_13_0
      config: id
      split: test
      args: id
    metrics:
    - type: wer
      value: 0.3274336283185841
      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. -->

# wav2vec2-xlsr-53-CV-demo-google-colab-Ezra_William_Prod17

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: 0.3395
- Wer: 0.3274

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 2.9137        | 1.0   | 278  | 2.8202          | 1.0    |
| 0.8546        | 2.0   | 556  | 0.6314          | 0.6728 |
| 0.4738        | 3.0   | 834  | 0.4380          | 0.4837 |
| 0.3338        | 4.0   | 1112 | 0.4024          | 0.4490 |
| 0.2557        | 5.0   | 1390 | 0.3622          | 0.4295 |
| 0.1972        | 6.0   | 1668 | 0.3381          | 0.3795 |
| 0.1644        | 7.0   | 1946 | 0.3632          | 0.3706 |
| 0.1442        | 8.0   | 2224 | 0.3352          | 0.3578 |
| 0.1287        | 9.0   | 2502 | 0.3441          | 0.3496 |
| 0.1122        | 10.0  | 2780 | 0.3501          | 0.3437 |
| 0.1035        | 11.0  | 3058 | 0.3389          | 0.3322 |
| 0.0961        | 12.0  | 3336 | 0.3395          | 0.3274 |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.2.2+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1