training_artifacts/README.md

microsoft/codebert-base Script Detector

Summary

Field	Value
Base model	microsoft/codebert-base
Phase	phase1
Target repo	HID-APP/script-detector-microsoft-codebert-base
Datasets	HID-APP/All-combined
Text column	text
Epochs	3.0000
Max length	512
Train batch size	4
Eval batch size	8
Gradient accumulation steps	4
Learning rate	0.0000
Precision	fp16
Optimizer	adamw_torch
Dataloader workers	0
Gradient checkpointing	False
Group by length	True
LoRA enabled	False

Dataset Sources

Source	Type	Revision	Fingerprint
HID-APP/All-combined	huggingface	default	81f16d3fdbb4f97d3574f5c78bce8ada7b15c9ccd625913daa095cae6d545d67

Training And Validation History

Epoch	Step	Train Loss	Eval Loss	Accuracy	Precision	Recall	F1
1.0000	373	3.2531
1.0000	373		0.5277	0.8353	0.8144	0.9806	0.8898
2.0000	746	2.7352
2.0000	746		0.5214	0.8291	0.8015	0.9943	0.8875
3.0000	1119	2.6190
3.0000	1119		0.5194	0.8360	0.8383	0.9396	0.8860

Final Test Summary

Split	Accuracy	Malicious Precision	Malicious Recall	Malicious F1	Loss
test	0.7846	0.7636	0.9598	0.8505	0.7020

Final Test Classification Report

Class	Precision	Recall	F1	Support
benign	0.8701	0.4753	0.6147	465.0000
malicious	0.7636	0.9598	0.8505	821.0000
macro avg	0.8168	0.7175	0.7326	1286.0000
weighted avg	0.8021	0.7846	0.7653	1286.0000
accuracy			0.7846

Final Test Confusion Matrix

	Pred benign	Pred malicious
Actual benign	221	244
Actual malicious	33	788

Final Test Grouped By Original Sample

Chunk rows: 1286; original samples: 1286.

Pooling	Original Samples	Accuracy	Malicious Precision	Malicious Recall	Malicious F1
max_pool	1286	0.7846	0.7636	0.9598	0.8505
mean_pool	1286	0.7846	0.7636	0.9598	0.8505