learning_rate: 1.5e-05
train_batch_size: 8
eval_batch_size: 8
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
num_epochs: 25

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.6359	1.0	450	0.5458	0.7809	0.7705
0.4368	2.0	900	0.5841	0.8076	0.8009
0.2974	3.0	1350	0.8080	0.8042	0.7960
0.197	4.0	1800	0.9819	0.8187	0.8123
0.122	5.0	2250	1.1943	0.8031	0.8003
0.0603	6.0	2700	1.4507	0.8065	0.8052
0.0231	7.0	3150	1.5382	0.8098	0.8068
0.0215	8.0	3600	1.5487	0.8176	0.8146
0.0303	9.0	4050	1.5812	0.8076	0.8063
0.0088	10.0	4500	1.6990	0.8131	0.8068
0.0135	11.0	4950	1.7569	0.8065	0.8045
0.0099	12.0	5400	1.7966	0.8154	0.8125
0.0255	13.0	5850	1.6712	0.8142	0.8112
0.0169	14.0	6300	1.8077	0.8053	0.8008
0.0196	15.0	6750	1.8089	0.8131	0.8094
0.0133	16.0	7200	1.8107	0.8131	0.8079
0.0109	17.0	7650	1.8350	0.8065	0.8037
0.0031	18.0	8100	1.8988	0.8042	0.8020
0.0047	19.0	8550	1.8727	0.8131	0.8091
0.002	20.0	9000	1.9545	0.8098	0.8066
0.0	21.0	9450	1.9588	0.8131	0.8099
0.0026	22.0	9900	1.9634	0.8087	0.8067
0.0	23.0	10350	2.0020	0.8131	0.8087
0.0	24.0	10800	2.0352	0.8031	0.8000
0.0004	25.0	11250	2.0373	0.8042	0.8013

LirihSetyo/results-mbg

results-mbg