cwe-parent-vulnerability-classification-roberta-base

This model is a fine-tuned version of roberta-base.

It achieves the following results on the evaluation set:

Model description

More information needed

More information needed

More information needed

The following hyperparameters were used during training:

learning_rate: 1e-05
train_batch_size: 32
eval_batch_size: 32
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: linear
num_epochs: 40

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1 Macro
3.2699	1.0	25	3.1492	0.0341	0.0055
3.1972	2.0	50	2.9909	0.0114	0.0064
3.1211	3.0	75	3.0017	0.0341	0.0140
3.0888	4.0	100	3.0223	0.2841	0.0463
2.9467	5.0	125	2.9608	0.0114	0.0018
2.9851	6.0	150	2.8743	0.1932	0.0641
2.9083	7.0	175	2.7687	0.375	0.0963
2.7652	8.0	200	2.7049	0.4318	0.1953
2.6893	9.0	225	2.5547	0.4886	0.1952
2.5636	10.0	250	2.4970	0.5682	0.3314
2.477	11.0	275	2.3499	0.6136	0.3790
2.2936	12.0	300	2.2659	0.6364	0.3949
2.1369	13.0	325	2.1758	0.625	0.4002
2.0615	14.0	350	2.1015	0.6477	0.4169
1.9548	15.0	375	1.9444	0.6932	0.3972
1.7943	16.0	400	1.8892	0.6818	0.4210
1.6619	17.0	425	1.8439	0.6818	0.4149
1.5391	18.0	450	1.7247	0.7159	0.4848
1.4415	19.0	475	1.6650	0.7273	0.4749
1.2834	20.0	500	1.5743	0.7727	0.5574
1.2245	21.0	525	1.5396	0.7614	0.5373
1.1629	22.0	550	1.5005	0.7614	0.5350
1.0894	23.0	575	1.4478	0.7614	0.5383
0.9755	24.0	600	1.4335	0.7841	0.5599
0.9271	25.0	625	1.4195	0.7841	0.5562
0.8761	26.0	650	1.3740	0.8182	0.6015
0.8312	27.0	675	1.3479	0.8295	0.6086
0.7523	28.0	700	1.3379	0.8295	0.5948
0.718	29.0	725	1.2991	0.8295	0.5948
0.6819	30.0	750	1.3059	0.8409	0.6047
0.6771	31.0	775	1.2650	0.8636	0.6167
0.6267	32.0	800	1.2905	0.8523	0.6252
0.6068	33.0	825	1.2559	0.875	0.6248
0.5811	34.0	850	1.2371	0.875	0.6248
0.5579	35.0	875	1.2231	0.875	0.6248
0.5385	36.0	900	1.2342	0.875	0.6248
0.5334	37.0	925	1.2255	0.875	0.6248
0.4868	38.0	950	1.2223	0.875	0.6248
0.5228	39.0	975	1.2078	0.875	0.6248
0.5325	40.0	1000	1.2101	0.875	0.6248