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---
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-XLS-R-Fleurs-demo-google-colab-Ezra_William_Prod11
  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: 0.35167772861356933
      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-XLS-R-Fleurs-demo-google-colab-Ezra_William_Prod11

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: 0.3642
- Wer: 0.3517

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 2.9446        | 1.0   | 278  | 2.9150          | 1.0    |
| 2.8395        | 2.0   | 556  | 2.1459          | 1.0    |
| 0.9822        | 3.0   | 834  | 0.5701          | 0.5534 |
| 0.6623        | 4.0   | 1112 | 0.4610          | 0.4699 |
| 0.5834        | 5.0   | 1390 | 0.4262          | 0.4213 |
| 0.4779        | 6.0   | 1668 | 0.4003          | 0.3908 |
| 0.4511        | 7.0   | 1946 | 0.3802          | 0.3731 |
| 0.4298        | 8.0   | 2224 | 0.3814          | 0.3657 |
| 0.4029        | 9.0   | 2502 | 0.3637          | 0.3575 |
| 0.3807        | 10.0  | 2780 | 0.3642          | 0.3517 |


### Framework versions

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