---
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: mascir_fr_wav2vec_version1000
  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. -->

# mascir_fr_wav2vec_version1000

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4677
- Wer: 0.37

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 5.3896        | 4.0   | 500  | 3.0842          | 1.0    |
| 1.6969        | 8.0   | 1000 | 0.6327          | 0.5956 |
| 0.3056        | 12.0  | 1500 | 0.5024          | 0.49   |
| 0.1441        | 16.0  | 2000 | 0.5241          | 0.45   |
| 0.091         | 20.0  | 2500 | 0.4997          | 0.44   |
| 0.0676        | 24.0  | 3000 | 0.5173          | 0.4456 |
| 0.0603        | 28.0  | 3500 | 0.4487          | 0.4122 |
| 0.0378        | 32.0  | 4000 | 0.4554          | 0.3933 |
| 0.0328        | 36.0  | 4500 | 0.4395          | 0.3822 |
| 0.0275        | 40.0  | 5000 | 0.4910          | 0.3889 |
| 0.0198        | 44.0  | 5500 | 0.4861          | 0.3722 |
| 0.019         | 48.0  | 6000 | 0.4677          | 0.37   |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.3
- Tokenizers 0.13.3