whisper-tiny-kor_eng_tiny_oc_lc

This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.5372
• Cer: 9.3870

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: 3e-05
• train_batch_size: 12
• eval_batch_size: 6
• 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: linear
• lr_scheduler_warmup_steps: 500
• training_steps: 4000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Cer
0.456	9.0909	100	0.3689	6.9923
0.0231	18.1818	200	0.4318	6.7050
0.0032	27.2727	300	0.4535	5.7471
0.0022	36.3636	400	0.4137	6.0345
0.0127	45.4545	500	0.5129	7.3755
0.0067	54.5455	600	0.4777	8.1418
0.0036	63.6364	700	0.4908	7.8544
0.0001	72.7273	800	0.4888	7.4713
0.0001	81.8182	900	0.4935	7.4713
0.0	90.9091	1000	0.4974	7.4713
0.0	100.0	1100	0.5003	6.8966
0.0	109.0909	1200	0.5032	6.8966
0.0	118.1818	1300	0.5060	6.8966
0.0	127.2727	1400	0.5084	6.8966
0.0	136.3636	1500	0.5106	6.6092
0.0	145.4545	1600	0.5125	6.6092
0.0	154.5455	1700	0.5143	6.6092
0.0	163.6364	1800	0.5161	6.6092
0.0	172.7273	1900	0.5174	6.7050
0.0	181.8182	2000	0.5190	6.7050
0.0	190.9091	2100	0.5211	6.7050
0.0	200.0	2200	0.5232	6.7050
0.0	209.0909	2300	0.5248	6.7050
0.0	218.1818	2400	0.5263	6.8966
0.0	227.2727	2500	0.5277	6.8966
0.0	236.3636	2600	0.5287	6.8966
0.0	245.4545	2700	0.5298	6.8966
0.0	254.5455	2800	0.5309	6.8966
0.0	263.6364	2900	0.5317	6.8966
0.0	272.7273	3000	0.5326	6.8966
0.0	281.8182	3100	0.5333	6.8966
0.0	290.9091	3200	0.5341	6.8966
0.0	300.0	3300	0.5348	6.8966
0.0	309.0909	3400	0.5350	6.8966
0.0	318.1818	3500	0.5359	9.3870
0.0	327.2727	3600	0.5362	9.3870
0.0	336.3636	3700	0.5365	9.3870
0.0	345.4545	3800	0.5366	9.3870
0.0	354.5455	3900	0.5370	9.3870
0.0	363.6364	4000	0.5372	9.3870

Framework versions

• Transformers 4.51.3
• Pytorch 2.6.0+cu126
• Datasets 3.5.0
• Tokenizers 0.21.1