---
license: apache-2.0
base_model: EzraWilliam/XLS-R-demo-google-colab-Ezra_William_Prod_3
tags:
- generated_from_trainer
datasets:
- common_voice_13_0
metrics:
- wer
model-index:
- name: XLS-R-demo-google-colab-Ezra_William_Prod_3
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_13_0
      type: common_voice_13_0
      config: id
      split: validation
      args: id
    metrics:
    - name: Wer
      type: wer
      value: 0.5589213319364096
---

<!-- 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_3

This model is a fine-tuned version of [EzraWilliam/XLS-R-demo-google-colab-Ezra_William_Prod_3](https://huggingface.co/EzraWilliam/XLS-R-demo-google-colab-Ezra_William_Prod_3) on the common_voice_13_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6384
- Wer: 0.5589

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 2.1618        | 1.0   | 121  | 1.3936          | 0.9716 |
| 1.4458        | 2.0   | 242  | 0.9181          | 0.7821 |
| 1.0146        | 3.0   | 363  | 0.7892          | 0.7048 |
| 0.8449        | 4.0   | 484  | 0.7344          | 0.6507 |
| 0.652         | 5.0   | 605  | 0.6840          | 0.6268 |
| 0.593         | 6.0   | 726  | 0.6598          | 0.5980 |
| 0.5549        | 7.0   | 847  | 0.6494          | 0.5817 |
| 0.5206        | 8.0   | 968  | 0.6572          | 0.5759 |
| 0.4958        | 9.0   | 1089 | 0.6376          | 0.5646 |
| 0.4683        | 10.0  | 1210 | 0.6384          | 0.5589 |


### Framework versions

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