This model is a fine-tuned version of openai/whisper-large-v3-turbo on the ntnu-smil/lttc-rebalanced-1-split dataset. It achieves the following results on the evaluation set:

Loss: 3.9922
Wer: 39.7321
Cer: 25.9187

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: 0.0005
train_batch_size: 4
eval_batch_size: 8
seed: 42
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Wer	Cer
0.0378	1.0	18	3.6518	40.3159	26.1279
0.0389	2.0	36	3.8285	40.0412	26.6444
0.0023	3.0	54	4.0319	40.4876	26.5529
0.0021	4.0	72	3.9976	39.3544	25.5656
0.0004	5.0	90	3.9922	39.7321	25.9187

Framework versions

PEFT 0.13.2
Transformers 4.46.3
Pytorch 2.2.0+cu121
Datasets 3.1.0
Tokenizers 0.20.3

ntnu-smil/whisper-large-v3-turbo-score-5-rebalanced-1-merged

whisper-large-v3-turbo-score-5-rebalanced-1

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

ntnu-smil/
whisper-large-v3-turbo-score-5-rebalanced-1-merged