README.md

---
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_Prod18
  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: 0.4212758112094395
      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_Prod18

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: 0.4870
- Wer: 0.4213

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 2.8991        | 1.0   | 278  | 2.8268          | 1.0    |
| 0.7566        | 2.0   | 556  | 0.6085          | 0.6369 |
| 0.4602        | 3.0   | 834  | 0.4967          | 0.5786 |
| 0.3297        | 4.0   | 1112 | 0.4746          | 0.4981 |
| 0.2545        | 5.0   | 1390 | 0.4570          | 0.4814 |
| 0.2098        | 6.0   | 1668 | 0.4639          | 0.4817 |
| 0.1765        | 7.0   | 1946 | 0.4796          | 0.4663 |
| 0.1568        | 8.0   | 2224 | 0.4876          | 0.4485 |
| 0.1514        | 9.0   | 2502 | 0.4651          | 0.4214 |
| 0.131         | 10.0  | 2780 | 0.4682          | 0.4276 |
| 0.1228        | 11.0  | 3058 | 0.4814          | 0.4234 |
| 0.1153        | 12.0  | 3336 | 0.4870          | 0.4213 |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1