learning_rate: 2e-05
train_batch_size: 32
eval_batch_size: 32
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
0.5889	1.0	87	0.5873	0.1408	0.5	0.1207
0.4707	2.0	174	0.4159	0.6512	0.7304	0.3966
0.3648	3.0	261	0.3671	0.6550	0.7572	0.4483
0.2675	4.0	348	0.3692	0.7085	0.7779	0.4397
0.1929	5.0	435	0.3821	0.7077	0.7781	0.4483
0.1407	6.0	522	0.4573	0.7087	0.7753	0.4224
0.097	7.0	609	0.4498	0.7392	0.8005	0.4569
0.0603	8.0	696	0.4655	0.7396	0.8002	0.4483
0.0455	9.0	783	0.4833	0.7472	0.8075	0.4483
0.0277	10.0	870	0.5366	0.7338	0.7972	0.4655
0.0254	11.0	957	0.5452	0.7429	0.8051	0.4569
0.0138	12.0	1044	0.5668	0.7460	0.8062	0.4655
0.0128	13.0	1131	0.5460	0.7566	0.8089	0.4828
0.0072	14.0	1218	0.5875	0.7551	0.8117	0.4828
0.0058	15.0	1305	0.6071	0.7474	0.8038	0.4655
0.0064	16.0	1392	0.5952	0.7531	0.8120	0.4828
0.005	17.0	1479	0.5976	0.7468	0.8041	0.4655

Kuongan/cs221-xlnet-large-cased-eng-pt

cs221-xlnet-large-cased-eng-pt