---
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_Prod9
  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: 0.9842089507558749
      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_Prod9

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: 1.3012
- Wer: 0.9842

## 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: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log        | 1.0   | 39   | 2.8812          | 1.0    |
| No log        | 2.0   | 78   | 2.8688          | 1.0    |
| No log        | 3.0   | 117  | 2.8722          | 1.0    |
| No log        | 4.0   | 156  | 2.8640          | 1.0    |
| No log        | 5.0   | 195  | 2.8447          | 1.0    |
| No log        | 6.0   | 234  | 2.8468          | 1.0    |
| No log        | 7.0   | 273  | 2.8465          | 1.0    |
| No log        | 8.0   | 312  | 2.8488          | 1.0    |
| No log        | 9.0   | 351  | 2.8355          | 1.0    |
| No log        | 10.0  | 390  | 2.8167          | 1.0    |
| No log        | 11.0  | 429  | 2.8076          | 1.0    |
| No log        | 12.0  | 468  | 2.7065          | 1.0    |
| 2.9881        | 13.0  | 507  | 2.5506          | 1.0    |
| 2.9881        | 14.0  | 546  | 2.2657          | 1.0    |
| 2.9881        | 15.0  | 585  | 1.9921          | 1.0    |
| 2.9881        | 16.0  | 624  | 1.7390          | 1.0    |
| 2.9881        | 17.0  | 663  | 1.5309          | 1.0    |
| 2.9881        | 18.0  | 702  | 1.4300          | 0.9994 |
| 2.9881        | 19.0  | 741  | 1.3280          | 0.9938 |
| 2.9881        | 20.0  | 780  | 1.3012          | 0.9842 |


### Framework versions

- Transformers 4.39.1
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2