This model is a fine-tuned version of openai/whisper-large-v3 on the Common Voice 16.1 dataset. It achieves the following results on the evaluation set:

Loss: 0.1323
Wer: 11.7279

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: Adam with betas=(0.9,0.999) and epsilon=1e-08
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
0.1372	0.3652	1000	0.1810	16.0805
0.1103	0.7305	2000	0.1628	14.5458
0.0563	1.0957	3000	0.1513	12.9302
0.0657	1.4609	4000	0.1383	12.4198
0.0444	1.8262	5000	0.1323	11.7279

Framework versions

Transformers 4.40.1
Pytorch 2.2.2+cu121
Datasets 2.19.0
Tokenizers 0.19.1

ozguntosun/whisper-large-v3-tr

Whisper Large TR - Özgün Tosun

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

ozguntosun/
whisper-large-v3-tr