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).
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