freshpearYoon/train3

whisper_finetune

This model is a fine-tuned version of openai/whisper-base on the aihub_3 dataset. It achieves the following results on the evaluation set:

• Loss: 0.3587
• Cer: 11.8692
• Wer: 34.6801

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: 32
• eval_batch_size: 16
• 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	Cer	Validation Loss	Wer
0.267	0.4	500	11.9783	0.3521	35.1998
0.2392	0.8	1000	12.1614	0.3495	34.9449
0.171	1.2	1500	12.0633	0.3516	35.2048
0.1744	1.6	2000	0.3553	12.2091	35.0598
0.1722	2.0	2500	0.3515	12.0222	34.5426
0.1192	2.4	3000	0.3594	12.2281	35.4796
0.1249	2.8	3500	0.3609	12.0137	34.8949
0.0858	3.2	4000	0.3587	11.8692	34.6801

Framework versions

• Transformers 4.37.0.dev0
• Pytorch 1.12.1+cu113
• Datasets 2.15.0
• Tokenizers 0.15.0