learning_rate: 2e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Use 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_steps: 100
num_epochs: 20

Training Loss	Epoch	Step	Validation Loss	F1	Roc Auc	Accuracy
0.577	1.0	139	0.5832	0.4593	0.6262	0.1516
0.5274	2.0	278	0.5171	0.4943	0.6506	0.1805
0.429	3.0	417	0.3725	0.7256	0.7927	0.4188
0.3146	4.0	556	0.3735	0.7468	0.8089	0.4567
0.2192	5.0	695	0.3846	0.7625	0.8216	0.4729
0.167	6.0	834	0.4137	0.7541	0.8126	0.4585
0.0954	7.0	973	0.4414	0.7672	0.8222	0.4783
0.0668	8.0	1112	0.5105	0.7696	0.8271	0.4747
0.0299	9.0	1251	0.5573	0.7688	0.8263	0.4531
0.0258	10.0	1390	0.5910	0.7793	0.8366	0.4783
0.0132	11.0	1529	0.6008	0.7741	0.8298	0.4801
0.0082	12.0	1668	0.6108	0.7780	0.8340	0.4711
0.0054	13.0	1807	0.6386	0.7806	0.8356	0.4711
0.0033	14.0	1946	0.6429	0.7775	0.8325	0.4747
0.0025	15.0	2085	0.6464	0.7763	0.8314	0.4675
0.0028	16.0	2224	0.6440	0.7846	0.8368	0.4892
0.0029	17.0	2363	0.6455	0.7816	0.8344	0.4856
0.0029	18.0	2502	0.6496	0.7777	0.8316	0.4765
0.0023	19.0	2641	0.6500	0.7812	0.8347	0.4819

Kuongan/CS221-xlnet-large-cased-finetuned-semeval

CS221-xlnet-large-cased-finetuned-semeval