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
0.1521	1.0	94	0.2867	0.9876	0.6667	1.0	0.8	0.7429
0.3329	2.0	188	0.2071	0.9938	0.8333	1.0	0.9091	0.8784
0.0007	3.0	282	0.3956	0.9938	0.8333	1.0	0.9091	0.8784
0.0006	4.0	376	0.2064	0.9938	0.8333	1.0	0.9091	0.8784
0.0011	5.0	470	0.2164	0.9938	0.8333	1.0	0.9091	0.8784
0.1444	6.0	564	0.1770	0.9938	0.8333	1.0	0.9091	0.8784
0.0008	7.0	658	0.2748	0.9938	0.8333	1.0	0.9091	0.8784
0.0004	8.0	752	0.3262	0.9938	0.8333	1.0	0.9091	0.8784
0.1464	9.0	846	0.1098	0.9938	0.8333	1.0	0.9091	0.8784
0.0007	10.0	940	0.0274	0.9969	0.9167	1.0	0.9565	0.9408
0.0002	11.0	1034	0.1486	0.9969	0.9167	1.0	0.9565	0.9408
0.0057	12.0	1128	0.2701	0.9969	0.9167	1.0	0.9565	0.9408
0.0001	13.0	1222	0.2820	0.9969	0.9167	1.0	0.9565	0.9408

buelfhood/progpedia19_codeberta_ep30_bs16_lr1e-05_l512_s42_ppn_loss

progpedia19_codeberta_ep30_bs16_lr1e-05_l512_s42_ppn_loss