This model is a fine-tuned version of openai/whisper-base on the AIhub_foreign_dataset4 dataset. It achieves the following results on the evaluation set:

Loss: 0.9395
Cer: 48.1817

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: 2e-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: cosine
lr_scheduler_warmup_steps: 500
training_steps: 6000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Cer
1.0479	0.7299	1000	0.9942	53.5695
0.983	1.4599	2000	0.9553	50.5824
0.7329	2.1898	3000	0.9432	56.3785
0.7979	2.9197	4000	0.9299	48.6001
0.6956	3.6496	5000	0.9368	47.2723
0.5971	4.3796	6000	0.9395	48.1817

Framework versions

Transformers 4.51.0.dev0
Pytorch 2.6.0+cu124
Datasets 3.5.0
Tokenizers 0.21.1

jwh1449/whisper_base_test

whisper_base_test

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

jwh1449/
whisper_base_test