Edit model card

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).

Downloads last month
9
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Evaluation results