freshpearYoon/train4

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: 0.4807
• Cer: 14.7381
• Wer: 40.8215

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	Validation Loss	Cer	Wer
0.2038	0.4	500	0.4405	13.6475	39.1975
0.1892	0.8	1000	0.4491	14.5230	40.5892
0.1218	1.2	1500	0.4710	14.4216	40.2519
0.1227	1.6	2000	0.4879	14.3981	40.1969
0.1311	2.0	2500	0.4638	14.6655	40.9614
0.0945	2.4	3000	0.4783	14.6635	40.9190
0.0874	2.8	3500	0.4743	14.3360	40.4492
0.0759	3.2	4000	0.4807	14.7381	40.8215

Framework versions

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