metadata

library_name: transformers
language:
  - fr
license: apache-2.0
base_model: openai/whisper-small
tags:
  - generated_from_trainer
datasets:
  - IndabaxSenegal/asr-wolof-dataset
metrics:
  - wer
model-index:
  - name: Whisper Small WO - Team
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: ASR Wolof Dataset
          type: IndabaxSenegal/asr-wolof-dataset
          args: 'config: wo, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 78.44373118690858

Whisper Small WO - Team

This model is a fine-tuned version of openai/whisper-small on the ASR Wolof Dataset dataset. It achieves the following results on the evaluation set:

Loss: 0.1726
Wer: 78.4437

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: 8
seed: 42
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
training_steps: 4000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0965	1.5408	1000	0.1751	83.2067
0.0406	3.0817	2000	0.1761	78.6749
0.0192	4.6225	3000	0.1772	78.8612
0.0037	6.1633	4000	0.1726	78.4437

Framework versions

Transformers 4.46.3
Pytorch 2.4.0
Datasets 3.1.0
Tokenizers 0.20.0