---
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- generated_from_trainer
datasets:
- common_voice_13_0
metrics:
- wer
model-index:
- name: wav2vec2-xlsr-53-CV-demo-google-colab-Ezra_William_Prod13
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_13_0
      type: common_voice_13_0
      config: id
      split: test
      args: id
    metrics:
    - name: Wer
      type: wer
      value: 0.4344579646017699
---

<!-- 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_Prod13

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the common_voice_13_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4253
- Wer: 0.4345

## 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: 3e-05
- train_batch_size: 8
- 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 4.7051        | 1.0   | 556  | 2.9406          | 1.0    |
| 2.9144        | 2.0   | 1112 | 2.8497          | 1.0    |
| 2.7392        | 3.0   | 1668 | 1.2240          | 0.9763 |
| 1.5108        | 4.0   | 2224 | 0.6735          | 0.6265 |
| 0.9692        | 5.0   | 2780 | 0.5435          | 0.5472 |
| 0.8216        | 6.0   | 3336 | 0.5079          | 0.5058 |
| 0.7343        | 7.0   | 3892 | 0.4788          | 0.4822 |
| 0.6782        | 8.0   | 4448 | 0.4531          | 0.4569 |
| 0.6089        | 9.0   | 5004 | 0.4535          | 0.4520 |
| 0.5811        | 10.0  | 5560 | 0.4326          | 0.4381 |
| 0.5669        | 11.0  | 6116 | 0.4287          | 0.4366 |
| 0.5749        | 12.0  | 6672 | 0.4253          | 0.4345 |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2