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

Loss: 1.3566
Wer: 32.3600
Cer: 18.4747

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: 16
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
0.0483	1.0	190	1.2801	35.8640	20.7045
0.0503	2.0	380	1.3510	32.5318	20.3283
0.0033	3.0	570	1.2776	39.3336	22.9891
0.0007	4.0	760	1.3057	32.6692	18.6594
0.0002	5.0	950	1.3566	32.3600	18.4747

Framework versions

PEFT 0.14.0
Transformers 4.47.0
Pytorch 2.2.0+cu121
Datasets 3.1.0
Tokenizers 0.21.0

ntnu-smil/whisper-large-v3-turbo-augmented

whisper-large-v3-turbo-augmented

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

ntnu-smil/
whisper-large-v3-turbo-augmented