README.md

metadata

language:
  - en
base_model: whisper
tags:
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_13_0
metrics:
  - wer
model-index:
  - name: 'IA4GOOD '
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 1
          type: mozilla-foundation/common_voice_13_0
          config: fr
          split: test
          args: fr
        metrics:
          - name: Wer
            type: wer
            value: 16.940544564986173

IA4GOOD

This model is a fine-tuned version of whisper on the Common Voice 1 dataset. It achieves the following results on the evaluation set:

• Loss: 0.3040
• Wer Ortho: 27.6287
• Wer: 16.9405

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: 1e-05
• 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: constant_with_warmup
• lr_scheduler_warmup_steps: 50
• training_steps: 500
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer Ortho	Wer
0.3182	0.29	500	0.3040	27.6287	16.9405

Framework versions

• Transformers 4.38.2
• Pytorch 2.2.1+cu121
• Datasets 2.18.0
• Tokenizers 0.15.2