This model is a fine-tuned version of openai/whisper-large-v3-turbo on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:

Loss: 0.1739
Wer: 15.6307

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: 1e-05
train_batch_size: 16
eval_batch_size: 8
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
training_steps: 5000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.1657	0.6154	1000	0.2519	21.1461
0.0993	1.2308	2000	0.2193	19.6685
0.0838	1.8462	3000	0.2031	18.6612
0.0574	2.4615	4000	0.1923	16.5399
0.0247	3.0769	5000	0.1739	15.6307

Framework versions

Transformers 4.47.0
Pytorch 2.4.1+cu121
Datasets 3.1.0
Tokenizers 0.21.0

Alperitoo/whisper-v3-turbo-common

Whisper Large V3 Turbo FT TR Telephonic - Alperitoo

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Alperitoo/
whisper-v3-turbo-common