README.md

metadata

license: apache-2.0
base_model: cifope/whisper-small-wolof
tags:
  - generated_from_trainer
datasets:
  - fleurs
metrics:
  - wer
model-index:
  - name: whisper-small-wolof
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: fleurs
          type: fleurs
          config: wo_sn
          split: test
          args: wo_sn
        metrics:
          - name: Wer
            type: wer
            value: 64.90514905149053

whisper-small-wolof

This model is a fine-tuned version of cifope/whisper-small-wolof on the fleurs dataset. It achieves the following results on the evaluation set:

• Loss: 1.4778
• Wer: 64.9051

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
• gradient_accumulation_steps: 4
• total_train_batch_size: 64
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500
• training_steps: 50
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
1.3863	1.4	50	1.4778	64.9051

Framework versions

• Transformers 4.35.2
• Pytorch 2.1.2+cu121
• Datasets 2.16.1
• Tokenizers 0.15.1