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 Loss	Epoch	Step	Validation Loss	Cer
0.5131	10.0	100	0.3638	8.4772
0.0156	20.0	200	0.4129	7.8493
0.0005	30.0	300	0.4288	6.9074
0.0002	40.0	400	0.4403	5.9655
0.0001	50.0	500	0.4499	5.9655
0.0001	60.0	600	0.4583	5.9655
0.0	70.0	700	0.4630	5.6515
0.0	80.0	800	0.4671	5.6515
0.0	90.0	900	0.4705	5.6515
0.0	100.0	1000	0.4732	5.6515
0.0	110.0	1100	0.4765	5.3375
0.0	120.0	1200	0.4780	5.3375
0.0	130.0	1300	0.4781	5.3375
0.0	140.0	1400	0.4796	5.3375
0.0	150.0	1500	0.4797	5.3375
0.0	160.0	1600	0.4802	5.3375
0.0	170.0	1700	0.4809	5.4945
0.0	180.0	1800	0.4807	5.4945
0.0	190.0	1900	0.4803	5.4945
0.0	200.0	2000	0.4797	5.4945
0.0	210.0	2100	0.4815	5.4945
0.0	220.0	2200	0.4820	5.4945
0.0	230.0	2300	0.4835	5.4945
0.0	240.0	2400	0.4839	5.4945
0.0	250.0	2500	0.4845	5.4945
0.0	260.0	2600	0.4849	5.4945
0.0	270.0	2700	0.4847	5.4945
0.0	280.0	2800	0.4852	5.4945
0.0	290.0	2900	0.4850	5.4945
0.0	300.0	3000	0.4861	5.4945
0.0	310.0	3100	0.4856	5.4945
0.0	320.0	3200	0.4857	5.4945
0.0	330.0	3300	0.4855	5.4945
0.0	340.0	3400	0.4854	5.4945
0.0	350.0	3500	0.4856	5.4945
0.0	360.0	3600	0.4851	5.4945
0.0	370.0	3700	0.4848	5.4945
0.0	380.0	3800	0.4859	5.4945
0.0	390.0	3900	0.4860	5.4945
0.0	400.0	4000	0.4856	5.4945

CianKim/whisper-tiny-kor_eng_tiny_oc_ob

whisper-tiny-kor_eng_tiny_oc_ob