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).
