| --- |
| license: apache-2.0 |
| task_categories: |
| - text-classification |
| language: |
| - en |
| tags: |
| - cybersecurity |
| - document-classification |
| - sft |
| - lora |
| size_categories: |
| - 10K<n<100K |
| --- |
| |
| # Beam Training Data |
|
|
| Supervised fine-tuning (SFT) dataset used to train **TorchSight Beam** — a |
| cybersecurity document classifier built by LoRA-fine-tuning Qwen 3.5 27B. |
|
|
| > Dobrovolskyi, I. *Security Document Classification with a Fine-Tuned Local |
| > Large Language Model: Benchmark Data and an Open-Source System.* Journal of |
| > Information Security and Applications, 2026. |
|
|
| ## Dataset |
|
|
| - **78,358 balanced samples** (95 / 5 split → 74,441 train + 3,917 validation) |
| - Alpaca format: `instruction`, `input`, `output` |
| - Output is a JSON array of findings, each with `category`, `subcategory`, |
| `severity`, `explanation` |
| - Stratified across 7 categories × 51 subcategories |
|
|
| ## Composition |
|
|
| The initial corpus contained 116,956 raw samples drawn from 13 publicly |
| available sources. To remove the NVD-dominated skew, each subcategory was |
| capped at 5,000 samples and underrepresented subcategories were augmented with |
| GPT-4–generated synthetic data and hard-negative boundary cases. |
|
|
| | Source | Raw | Balanced | License | Categories | |
| |---|---:|---:|---|---| |
| | NVD CVE Database | 50,000 | 8,475 | Public domain | `malicious.exploit` | |
| | Synthetic augmentation| 33,100 | 39,754 | Generated (GPT-4) | All categories | |
| | Hard negatives | 6,400 | 6,134 | Generated (GPT-4) | Boundary cases | |
| | AI4Privacy | 5,000 | 4,851 | Apache 2.0 | `pii.*` | |
| | Fenrir v2.0 | 5,000 | 4,573 | Apache 2.0 | `malicious.*` | |
| | SEC EDGAR | 3,000 | 3,000 | Public domain | `financial.*` | |
| | SecLists | 3,229 | 1,708 | MIT | `malicious.injection` | |
| | Phishing Dataset | 3,000 | 2,796 | Apache 2.0 | `malicious.phishing` | |
| | NIST Training | 3,000 | 2,761 | Public domain | `safe.documentation` | |
| | Enron Email Corpus | 2,000 | 1,902 | Public domain | `pii.*`, `credentials.*` | |
| | MITRE ATT&CK v14 | 1,620 | 871 | Royalty-free | `malicious.malware` | |
| | Loghub | 1,280 | 1,280 | Research-free | `safe.config` | |
| | Other (3 sources) | 327 | 253 | Permissive | Multiple | |
| | **Total** | **116,956** | **78,358** | | | |
|
|
| All sources have been verified safe for AI training. Copyleft-licensed |
| (GPL/LGPL) and ShareAlike-licensed (CC BY-SA) materials are excluded so the |
| corpus is suitable for commercial training use. |
|
|
| Of the final 78,358 samples, 39,754 (50.7%) are GPT-4–generated synthetic |
| augmentation and 6,134 (7.8%) are hard-negative boundary cases. The remaining |
| 32,470 (41.5%) come from the 13 external sources listed above. |
|
|
| ## Structure |
|
|
| ``` |
| sft/ |
| ├── train_alpaca.jsonl # 74,441 samples |
| └── val_alpaca.jsonl # 3,917 samples |
| processed/ # intermediate per-source files |
| synthetic/ # GPT-4 generations and hard negatives |
| ``` |
|
|
| ## LoRA training configuration |
|
|
| | Parameter | Value | |
| |---|---| |
| | Base model | Qwen 3.5 27B (dense) | |
| | LoRA rank (r) | 128 | |
| | LoRA alpha (α) | 256 | |
| | Target modules | q/k/v/o_proj, gate/up/down_proj | |
| | Dropout | 0.05 | |
| | Learning rate | 2 × 10⁻⁵, cosine decay, 10% warmup | |
| | Effective batch size | 16 (4 × 4 gradient accumulation) | |
| | Epochs | 5 | |
| | Precision | bf16 | |
| | Max sequence length | 4,096 tokens | |
| | Hardware | 8× NVIDIA A100 80GB SXM4 | |
| | Wall-clock time | 10.5 hours | |
|
|
| Library versions: `trl == 0.11.4`, `transformers == 4.45.2`, `peft == 0.13.2`. |
|
|
| ## License |
|
|
| Apache 2.0. |
|
|
| ## Companion artifacts |
|
|
| - Benchmark: [`torchsight/cybersecurity-classification-benchmark`](https://huggingface.co/datasets/torchsight/cybersecurity-classification-benchmark) |
| - Models: [`torchsight/beam-q4_K_M`](https://huggingface.co/torchsight/beam-q4_K_M), |
| [`torchsight/beam-q8_0`](https://huggingface.co/torchsight/beam-q8_0), |
| [`torchsight/beam-f16`](https://huggingface.co/torchsight/beam-f16) |
| - Source: [github.com/IvanDobrovolsky/torchsight](https://github.com/IvanDobrovolsky/torchsight) |
|
|
