---
license: apache-2.0
base_model: jonatasgrosman/wav2vec2-large-xlsr-53-french
tags:
- generated_from_trainer
datasets:
- minds14
metrics:
- wer
model-index:
- name: French_asr_model
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: minds14
      type: minds14
      config: fr-FR
      split: None
      args: fr-FR
    metrics:
    - name: Wer
      type: wer
      value: 0.3484848484848485
---

<!-- 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. -->

# French_asr_model

This model is a fine-tuned version of [jonatasgrosman/wav2vec2-large-xlsr-53-french](https://huggingface.co/jonatasgrosman/wav2vec2-large-xlsr-53-french) on the minds14 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2408
- Wer: 0.3485

## 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
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 250
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch    | Step | Validation Loss | Wer    |
|:-------------:|:--------:|:----:|:---------------:|:------:|
| 0.0049        | 333.3333 | 500  | 1.1485          | 0.3485 |
| 0.0015        | 666.6667 | 1000 | 1.2408          | 0.3485 |


### Framework versions

- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1