learning_rate: 2.5e-05
train_batch_size: 16
eval_batch_size: 32
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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	F1	Precision	Recall	Accuracy
0.0587	1.5385	20	0.2010	0.0	0.0	0.0	0.9422
0.0916	3.0769	40	0.1425	0.2535	0.3108	0.2141	0.9535
0.0571	4.6154	60	0.1251	0.3194	0.3126	0.3265	0.9594
0.0289	6.1538	80	0.1168	0.4129	0.3915	0.4368	0.9651
0.0144	7.6923	100	0.1160	0.4527	0.4473	0.4584	0.9671
0.0041	9.2308	120	0.1040	0.5464	0.4822	0.6303	0.9713
0.0036	10.7692	140	0.1011	0.5780	0.5410	0.6205	0.9728
0.0026	12.3077	160	0.1000	0.6219	0.5760	0.6757	0.9743
0.0025	13.8462	180	0.1004	0.6285	0.5867	0.6768	0.9749
0.003	15.3846	200	0.1018	0.6373	0.5989	0.6811	0.9753
0.0032	16.9231	220	0.1034	0.6484	0.6117	0.6897	0.9758
0.0022	18.4615	240	0.1035	0.6529	0.6105	0.7016	0.9760
0.0002	20.0	260	0.1044	0.6552	0.6154	0.7005	0.9763
0.0021	21.5385	280	0.1046	0.6629	0.6240	0.7070	0.9767
0.0029	23.0769	300	0.1041	0.6643	0.6215	0.7135	0.9764
0.0043	24.6154	320	0.1046	0.6663	0.6234	0.7157	0.9765
0.0012	26.1538	340	0.1052	0.6673	0.6251	0.7157	0.9765
0.0014	27.6923	360	0.1054	0.6680	0.6255	0.7168	0.9765
0.0009	29.2308	380	0.1055	0.6677	0.6249	0.7168	0.9765

prinsINT/deberta-v3-base-uner-down200

deberta-v3-base-uner-down200