This model is a fine-tuned version of openai/whisper-small on the ru_audiobooks_sova dataset. It achieves the following results on the evaluation set:

Loss: 0.1732
Wer: 14.9319

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: 1000
num_epochs: 3
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.2325	0.3501	4000	0.2328	20.7527
0.1867	0.7002	8000	0.2006	18.3470
0.0968	1.0503	12000	0.1889	16.9944
0.1109	1.4004	16000	0.1805	16.6653
0.0947	1.7505	20000	0.1746	15.7622
0.0435	2.1007	24000	0.1756	15.4416
0.0566	2.4508	28000	0.1756	15.1253
0.0462	2.8009	32000	0.1732	14.9319

Framework versions

Transformers 4.44.2
Pytorch 2.4.1+cu124
Datasets 2.21.0
Tokenizers 0.19.1

Stepler/whisper-large-v3-small-v6.0

Whisper Small RU (Phone) v6 - Stepler

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Stepler/
whisper-large-v3-small-v6.0