learning_rate: 2e-05
train_batch_size: 32
eval_batch_size: 64
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: linear
num_epochs: 10

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1	Balanced Accuracy	Mcc
No log	1.0	99	0.2730	0.9059	0.9305	0.8788	0.9039	0.9061	0.8130
0.4532	2.0	198	0.2610	0.9059	0.9548	0.8535	0.9013	0.9063	0.8165
0.2683	3.0	297	0.2622	0.9008	0.9441	0.8535	0.8966	0.9011	0.8054
0.202	4.0	396	0.2914	0.9109	0.9179	0.9040	0.9109	0.9110	0.8220
0.1308	5.0	495	0.3012	0.9135	0.9362	0.8889	0.9119	0.9137	0.8281
0.0856	6.0	594	0.3709	0.8906	0.8818	0.9040	0.8928	0.8905	0.7814
0.0622	7.0	693	0.4141	0.8957	0.8905	0.9040	0.8972	0.8956	0.7914
0.0366	8.0	792	0.4711	0.8957	0.8720	0.9293	0.8998	0.8954	0.7930
0.0262	9.0	891	0.4318	0.8982	0.8990	0.8990	0.8990	0.8982	0.7964
0.0145	10.0	990	0.4440	0.8957	0.8867	0.9091	0.8978	0.8956	0.7916

hurtmongoose/bert-base-detect-jailbreak

bert-base-detect-jailbreak