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	0.5	2	10.6101	0.0241	10.6077	3.2569
No log	1.0	4	8.4571	0.0	8.4550	2.9078
No log	1.5	6	6.3590	0.0	6.3574	2.5214
No log	2.0	8	5.0383	0.0528	5.0371	2.2443
5.8376	2.5	10	3.9819	0.0079	3.9809	1.9952
5.8376	3.0	12	3.1453	0.0	3.1444	1.7733
5.8376	3.5	14	2.3039	0.1224	2.3035	1.5177
5.8376	4.0	16	1.9498	0.0921	1.9495	1.3962
5.8376	4.5	18	1.6207	0.0315	1.6206	1.2730
2.2324	5.0	20	1.3803	0.0	1.3803	1.1749
2.2324	5.5	22	1.4148	0.0	1.4149	1.1895
2.2324	6.0	24	1.4141	0.0	1.4141	1.1892
2.2324	6.5	26	1.2084	0.0	1.2086	1.0994
2.2324	7.0	28	1.1624	0.0211	1.1625	1.0782
1.7125	7.5	30	1.2010	0.0521	1.2010	1.0959
1.7125	8.0	32	1.1460	0.0307	1.1460	1.0705
1.7125	8.5	34	1.2599	0.0690	1.2598	1.1224

genki10/ASAP_FineTuningBERT_AugV8_k4_task1_organization_fold1

ASAP_FineTuningBERT_AugV8_k4_task1_organization_fold1