README.md

metadata

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

French_asr_model

This model is a fine-tuned version of 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