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metadata
language:
  - en
license: apache-2.0
base_model: openai/whisper-base.en
tags:
  - nyansapo_ai-asr-leaderboard
  - generated_from_trainer
datasets:
  - NyansapoAI/azure-dataset
metrics:
  - wer
model-index:
  - name: whisper-base-bungoma.en
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Azure-dataset
          type: NyansapoAI/azure-dataset
          args: 'split: test'
        metrics:
          - name: Wer
            type: wer
            value: 25.28041415012942

whisper-base-bungoma.en

This model is a fine-tuned version of openai/whisper-base.en on the Azure-dataset dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0636
  • Wer: 25.2804

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: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 250
  • training_steps: 1000

Training results

Training Loss Epoch Step Validation Loss Wer
0.7399 1.38 250 0.2390 29.3356
0.2829 2.76 500 0.0774 21.8292
0.1573 4.14 750 0.0921 22.8645
0.1373 5.52 1000 0.0636 25.2804

Framework versions

  • Transformers 4.39.1
  • Pytorch 2.2.1
  • Datasets 2.18.0
  • Tokenizers 0.15.2