# 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 |