---
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: fr_only
  results: []
---

<!-- 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. -->

# fr_only

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1454
- Wer: 0.6672
- Cer: 0.3732

## 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: 0.0003
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 4.2678        | 0.8   | 500  | 3.9064          | 1.0    | 1.0    |
| 3.8874        | 1.61  | 1000 | 3.8322          | 1.0    | 1.0    |
| 3.7809        | 2.41  | 1500 | 3.5061          | 0.9737 | 0.8809 |
| 2.9215        | 3.21  | 2000 | 2.4683          | 0.9685 | 0.6577 |
| 2.3508        | 4.01  | 2500 | 2.1271          | 0.9144 | 0.6212 |
| 2.0152        | 4.82  | 3000 | 1.8754          | 0.8794 | 0.5677 |
| 1.6777        | 5.62  | 3500 | 1.5346          | 0.7830 | 0.4904 |
| 1.4068        | 6.42  | 4000 | 1.3605          | 0.7419 | 0.4583 |
| 1.1826        | 7.22  | 4500 | 1.2643          | 0.6912 | 0.4349 |
| 0.9938        | 8.03  | 5000 | 1.1641          | 0.7039 | 0.3977 |
| 0.7796        | 8.83  | 5500 | 1.1441          | 0.6934 | 0.3865 |
| 0.6479        | 9.63  | 6000 | 1.1454          | 0.6672 | 0.3732 |


### Framework versions

- Transformers 4.36.2
- Pytorch 1.13.0+cu116
- Datasets 2.15.0
- Tokenizers 0.15.2