---
license: apache-2.0
tags:
- generated_from_trainer
base_model: facebook/wav2vec2-large-xlsr-53
datasets:
- common_voice_13_0
metrics:
- wer
model-index:
- name: wav2vec2-xlsr-53-CV-demo-google-colab-Ezra_William_Prod12
  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: 0.29217367256637167
      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_Prod12

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: 0.3025
- Wer: 0.2922

## 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: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 2.9131        | 1.0   | 464  | 2.9568          | 1.0    |
| 1.0005        | 2.0   | 928  | 0.6123          | 0.5699 |
| 0.5939        | 3.0   | 1392 | 0.4082          | 0.4204 |
| 0.4569        | 4.0   | 1856 | 0.3475          | 0.3725 |
| 0.4151        | 5.0   | 2320 | 0.3333          | 0.3413 |
| 0.3655        | 6.0   | 2784 | 0.3223          | 0.3234 |
| 0.3351        | 7.0   | 3248 | 0.3163          | 0.3078 |
| 0.3103        | 8.0   | 3712 | 0.3045          | 0.2956 |
| 0.3063        | 9.0   | 4176 | 0.3001          | 0.2900 |
| 0.3072        | 10.0  | 4640 | 0.3025          | 0.2922 |


### Framework versions

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