README.md

metadata

license: apache-2.0
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - kul-speech-lab/CGN
metrics:
  - wer
model-index:
  - name: Whisper Large CGN
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: kul-speech-lab/CGN
          type: kul-speech-lab/CGN
          config: cgn-dev.py
          split: test
        metrics:
          - name: Wer
            type: wer
            value: 9.6159

Whisper Large CGN

This model is a fine-tuned version of openai/whisper-large-v2 on the kul-speech-lab/CGN dataset. It achieves the following results on the evaluation set:

• Loss: 0.23932012915611267
• Wer: 9.615871912312803

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 1e-05
• train_batch_size: 32
• eval_batch_size: 16
• gradient_accumulation_steps: 2
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500
• training_steps: 15000
• mixed_precision_training: Native AMP

Framework versions

• Transformers 4.26.0.dev0
• Pytorch 1.13.0
• Datasets 2.7.1.dev0
• Tokenizers 0.13.2

Whisper large model finetuned on Flemish part of Corpus Gesproken Nederlands (CGN).