This model is a fine-tuned version of openai/whisper-large-v3 on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:

Loss: 0.5842
Wer: 188.0606

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: 4000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0003	28.5714	1000	0.4718	546.6835
0.0	57.1429	2000	0.5506	175.4264
0.0	85.7143	3000	0.5751	185.3759
0.0	114.2857	4000	0.5842	188.0606

Framework versions

Transformers 4.42.0.dev0
Pytorch 1.12.0
Datasets 2.20.0
Tokenizers 0.19.1

Drahokma/whisper-large-v3-kz

Whisper Large v3 Kazakh

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Drahokma/
whisper-large-v3-kz