lalok/gyeongsan_address_firestation_ko_14000hr_M

This model is a fine-tuned version of openai/whisper-medium on the lalok/gyeongsan_address_firestation_ko_14000hr dataset. It achieves the following results on the evaluation set:

• Loss: 0.2375
• Cer: 16.0569

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: 100
• training_steps: 10000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Cer
0.2677	0.0908	5000	0.2662	17.8377
0.2062	0.1816	10000	0.2375	16.0569

Framework versions

• Transformers 4.41.2
• Pytorch 2.2.2+cu121
• Datasets 2.19.2
• Tokenizers 0.19.1