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---
license: apache-2.0
tags:
- generated_from_trainer
base_model: facebook/wav2vec2-large-xlsr-53
datasets:
- xtreme_s
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: xtreme_s
      type: xtreme_s
      config: fleurs.id_id
      split: test
      args: fleurs.id_id
    metrics:
    - type: wer
      value: 1.0
      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 xtreme_s dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3184
- Wer: 1.0

## 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: 0.001
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:---:|
| 3.6308        | 1.0   | 126  | 2.8604          | 1.0 |
| 2.8784        | 2.0   | 252  | 2.8477          | 1.0 |
| 2.8707        | 3.0   | 378  | 2.8556          | 1.0 |
| 2.8589        | 4.0   | 504  | 2.8471          | 1.0 |
| 2.8518        | 5.0   | 630  | 2.8402          | 1.0 |
| 2.8472        | 6.0   | 756  | 2.8495          | 1.0 |
| 2.8414        | 7.0   | 882  | 2.8303          | 1.0 |
| 2.8215        | 8.0   | 1008 | 2.7800          | 1.0 |
| 2.7687        | 9.0   | 1134 | 2.6640          | 1.0 |
| 2.5326        | 10.0  | 1260 | 2.3184          | 1.0 |


### Framework versions

- Transformers 4.39.2
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2