learning_rate: 2e-05
train_batch_size: 64
eval_batch_size: 64
seed: 42
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 100

Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	0.25	2	10.8084	0.0252	10.8060	3.2873
No log	0.5	4	8.5966	0.0	8.5944	2.9316
No log	0.75	6	6.3101	0.0	6.3085	2.5117
No log	1.0	8	5.0487	0.0676	5.0476	2.2467
5.5629	1.25	10	4.0465	0.0079	4.0455	2.0114
5.5629	1.5	12	3.1947	0.0	3.1940	1.7872
5.5629	1.75	14	2.3820	0.0344	2.3815	1.5432
5.5629	2.0	16	2.0304	0.1357	2.0301	1.4248
5.5629	2.25	18	1.8435	0.0491	1.8433	1.3577
2.1103	2.5	20	1.4209	0.0315	1.4209	1.1920
2.1103	2.75	22	1.2281	0.0211	1.2282	1.1082
2.1103	3.0	24	1.4696	0.0211	1.4695	1.2122
2.1103	3.25	26	1.7809	0.0301	1.7807	1.3344
2.1103	3.5	28	1.6030	0.0418	1.6028	1.2660
1.7334	3.75	30	1.0980	0.0315	1.0980	1.0479
1.7334	4.0	32	0.9716	0.0434	0.9718	0.9858
1.7334	4.25	34	1.2620	0.0289	1.2620	1.1234
1.7334	4.5	36	1.7684	0.0315	1.7682	1.3297

genki10/ASAP_FineTuningBERT_AugV8_k10_task1_organization_fold1

ASAP_FineTuningBERT_AugV8_k10_task1_organization_fold1