learning_rate: 2e-05
train_batch_size: 32
eval_batch_size: 32
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: 10

Training Loss	Epoch	Step	Validation Loss	Precision Samples	Recall Samples	F1 Samples	Precision Macro	Recall Macro	F1 Macro	Precision Micro	Recall Micro	F1 Micro	Precision Weighted	Recall Weighted	F1 Weighted
No log	1.0	5	9.3895	1.0	0.0	0.0	1.0	0.3571	0.3571	1.0	0.0	0.0	1.0	0.0	0.0
8.4727	2.0	10	9.1240	1.0	0.0	0.0	1.0	0.3571	0.3571	1.0	0.0	0.0	1.0	0.0	0.0
8.4727	3.0	15	8.9313	0.475	0.475	0.475	0.9925	0.3714	0.3663	0.475	0.2135	0.2946	0.8879	0.2135	0.1375
7.9967	4.0	20	8.7771	0.475	0.475	0.475	0.9925	0.3714	0.3663	0.475	0.2135	0.2946	0.8879	0.2135	0.1375
7.9967	5.0	25	8.6665	0.475	0.475	0.475	0.9925	0.3714	0.3663	0.475	0.2135	0.2946	0.8879	0.2135	0.1375
7.6436	6.0	30	8.6018	0.475	0.475	0.475	0.9925	0.3714	0.3663	0.475	0.2135	0.2946	0.8879	0.2135	0.1375
7.6436	7.0	35	8.5536	0.475	0.475	0.475	0.9925	0.3714	0.3663	0.475	0.2135	0.2946	0.8879	0.2135	0.1375
7.4488	8.0	40	8.5164	0.475	0.475	0.475	0.9925	0.3714	0.3663	0.475	0.2135	0.2946	0.8879	0.2135	0.1375
7.4488	9.0	45	8.4947	0.475	0.475	0.475	0.9925	0.3714	0.3663	0.475	0.2135	0.2946	0.8879	0.2135	0.1375
7.3567	10.0	50	8.4863	0.475	0.475	0.475	0.9925	0.3714	0.3663	0.475	0.2135	0.2946	0.8879	0.2135	0.1375

g-assismoraes/deberta-semeval25_justEN08_fold4

deberta-semeval25_justEN08_fold4