learning_rate: 3e-05
train_batch_size: 8
eval_batch_size: 8
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: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 20
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss	F1	Roc Auc	Accuracy
0.0167	1.0	3115	0.2207	0.2035	0.5691	0.1071
0.0138	2.0	6230	0.2613	0.2091	0.5730	0.1083
0.0102	3.0	9345	0.3444	0.2249	0.5841	0.1147
0.0073	4.0	12460	0.6223	0.1944	0.5654	0.0991
0.0053	5.0	15575	0.6920	0.1973	0.5668	0.1004
0.0022	6.0	18690	0.7143	0.1983	0.5680	0.0996
0.0012	7.0	21805	0.7309	0.1968	0.5672	0.0993
0.0007	8.0	24920	0.7349	0.2035	0.5706	0.1031
0.0006	9.0	28035	0.7521	0.2064	0.5718	0.1070
0.0003	10.0	31150	0.7684	0.2039	0.5705	0.1033

DayCardoso/valueeval24-modern-bert-cos-initialfreeze-diff-lr

valueeval24-modern-bert-cos-initialfreeze-diff-lr