This model is a fine-tuned version of openai/whisper-small on the aihub adult speed changed dataset. It achieves the following results on the evaluation set:

Loss: 0.2582
Cer: 6.8433

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: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 50
num_epochs: 2
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Cer
0.314	0.13	100	0.2988	7.3426
0.2117	0.26	200	0.2714	7.1664
0.1585	0.39	300	0.2759	7.8654
0.1633	0.52	400	0.2599	7.3015
0.1411	0.64	500	0.2663	7.2192
0.1323	0.77	600	0.2674	7.1370
0.1354	0.9	700	0.2632	7.1781
0.082	1.03	800	0.2599	7.0841
0.0647	1.16	900	0.2590	6.9196
0.078	1.29	1000	0.2601	6.8961
0.0671	1.42	1100	0.2593	6.8198
0.0716	1.55	1200	0.2576	6.8609
0.0699	1.68	1300	0.2581	6.7493
0.0682	1.81	1400	0.2574	6.8785
0.0713	1.93	1500	0.2582	6.8433

Framework versions

Transformers 4.37.0.dev0
Pytorch 2.1.0+cu121
Datasets 2.15.0
Tokenizers 0.15.0

Gummybear05/whisper-small-ko-Yfreq_SA

whisper-small-ko-Yfreq_SA

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Gummybear05/
whisper-small-ko-Yfreq_SA