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
0.6922	1.0	21	0.6828	0.7971	0.9636	0.8154	0.8833	0.9126
0.6858	2.0	42	0.6773	0.7971	1.0	0.7971	0.8871	0.9274
0.6742	3.0	63	0.6408	0.8696	0.8727	0.96	0.9143	0.8978
0.588	4.0	84	0.4871	0.8261	0.7818	1.0	0.8776	0.8381
0.4632	5.0	105	0.2596	0.8986	0.8727	1.0	0.9320	0.9083
0.2506	6.0	126	0.4533	0.7101	0.6364	1.0	0.7778	0.7165
0.4264	7.0	147	0.1075	0.9855	0.9818	1.0	0.9908	0.9873
0.1983	8.0	168	0.1351	0.8986	0.8727	1.0	0.9320	0.9083
0.1002	9.0	189	0.0807	0.9710	0.9818	0.9818	0.9818	0.9818
0.1096	10.0	210	0.0615	0.9710	0.9636	1.0	0.9815	0.9745
0.0656	11.0	231	0.0461	0.9855	0.9818	1.0	0.9908	0.9873
0.0432	12.0	252	0.0442	0.9855	0.9818	1.0	0.9908	0.9873
0.0492	13.0	273	0.1025	0.9420	0.9273	1.0	0.9623	0.9485
0.0493	14.0	294	0.0659	0.9710	0.9636	1.0	0.9815	0.9745
0.0444	15.0	315	0.0691	0.9710	0.9636	1.0	0.9815	0.9745

buelfhood/irplag_codebert_ep30_bs16_lr1e-05_l512_s42_ppn_loss

irplag_codebert_ep30_bs16_lr1e-05_l512_s42_ppn_loss