---
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: 0.4441
- Wer: 0.3622

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log        | 2.0   | 250  | 4.6558          | 1.0    |
| 5.4653        | 4.0   | 500  | 3.1189          | 1.0    |
| 5.4653        | 6.0   | 750  | 1.3807          | 0.9344 |
| 1.6415        | 8.0   | 1000 | 0.6832          | 0.5689 |
| 1.6415        | 10.0  | 1250 | 0.4986          | 0.48   |
| 0.3065        | 12.0  | 1500 | 0.4968          | 0.4711 |
| 0.3065        | 14.0  | 1750 | 0.4470          | 0.4533 |
| 0.1441        | 16.0  | 2000 | 0.4832          | 0.4433 |
| 0.1441        | 18.0  | 2250 | 0.5433          | 0.45   |
| 0.0938        | 20.0  | 2500 | 0.4734          | 0.4344 |
| 0.0938        | 22.0  | 2750 | 0.4745          | 0.4111 |
| 0.0727        | 24.0  | 3000 | 0.4236          | 0.4044 |
| 0.0727        | 26.0  | 3250 | 0.4692          | 0.4133 |
| 0.0556        | 28.0  | 3500 | 0.4411          | 0.3967 |
| 0.0556        | 30.0  | 3750 | 0.4722          | 0.3822 |
| 0.0422        | 32.0  | 4000 | 0.4845          | 0.3978 |
| 0.0422        | 34.0  | 4250 | 0.4818          | 0.4    |
| 0.0325        | 36.0  | 4500 | 0.4638          | 0.3944 |
| 0.0325        | 38.0  | 4750 | 0.4737          | 0.38   |
| 0.0284        | 40.0  | 5000 | 0.4615          | 0.3822 |
| 0.0284        | 42.0  | 5250 | 0.4491          | 0.3722 |
| 0.0235        | 44.0  | 5500 | 0.4480          | 0.3744 |
| 0.0235        | 46.0  | 5750 | 0.4630          | 0.3711 |
| 0.0172        | 48.0  | 6000 | 0.4421          | 0.3644 |
| 0.0172        | 50.0  | 6250 | 0.4441          | 0.3622 |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.2
- Tokenizers 0.13.3