learning_rate: 1e-05
train_batch_size: 16
eval_batch_size: 16
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: 30

Training Loss	Epoch	Step	Validation Loss	Accuracy	Recall	Precision	F1	F Beta Score
0.6669	1.0	21	0.6282	0.8116	0.7636	1.0	0.8660	0.8235
0.5616	2.0	42	0.4538	0.7826	0.7636	0.9545	0.8485	0.8137
0.35	3.0	63	0.2366	0.9420	0.9273	1.0	0.9623	0.9485
0.1932	4.0	84	0.1208	0.9710	0.9636	1.0	0.9815	0.9745
0.1292	5.0	105	0.1733	0.9565	0.9818	0.9643	0.9730	0.9764
0.0714	6.0	126	0.0801	0.9565	0.9455	1.0	0.9720	0.9616
0.0792	7.0	147	0.0890	0.9565	0.9455	1.0	0.9720	0.9616
0.0668	8.0	168	0.0598	0.9710	0.9636	1.0	0.9815	0.9745
0.0706	9.0	189	0.0505	0.9710	0.9636	1.0	0.9815	0.9745
0.07	10.0	210	0.0728	0.9855	0.9818	1.0	0.9908	0.9873
0.0303	11.0	231	0.0476	0.9710	0.9636	1.0	0.9815	0.9745
0.0261	12.0	252	0.0715	0.9710	0.9636	1.0	0.9815	0.9745
0.0275	13.0	273	0.0524	0.9710	0.9636	1.0	0.9815	0.9745
0.0308	14.0	294	0.0676	0.9710	0.9636	1.0	0.9815	0.9745

buelfhood/irplag_graphcodebert_ep30_bs16_lr1e-05_l512_s42_ppn_loss

irplag_graphcodebert_ep30_bs16_lr1e-05_l512_s42_ppn_loss