---
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_Prod14
  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: 0.9997695427728613
      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_Prod14

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: 1.8240
- Wer: 0.9998

## 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: 0.003
- 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 2.8908        | 1.0   | 556  | 2.8658          | 1.0    |
| 2.8733        | 2.0   | 1112 | 2.8600          | 1.0    |
| 2.6756        | 3.0   | 1668 | 2.5449          | 1.0000 |
| 2.2847        | 4.0   | 2224 | 2.1842          | 1.0    |
| 2.2086        | 5.0   | 2780 | 2.0814          | 0.9999 |
| 2.1121        | 6.0   | 3336 | 2.0101          | 1.0    |
| 2.0778        | 7.0   | 3892 | 1.9459          | 1.0    |
| 1.9959        | 8.0   | 4448 | 1.9099          | 0.9999 |
| 1.981         | 9.0   | 5004 | 1.8806          | 0.9999 |
| 1.9512        | 10.0  | 5560 | 1.8475          | 0.9999 |
| 1.9468        | 11.0  | 6116 | 1.8366          | 0.9998 |
| 1.9164        | 12.0  | 6672 | 1.8240          | 0.9998 |


### Framework versions

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