Create README.md

README.md

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+---
+license: odc-by
+task_categories:
+- text-generation
+language:
+- en
+pretty_name: Primus-FineWeb
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: data/*
+tags:
+- cybersecurity
+- pretraining
+- FineWeb
+size_categories:
+- 1M<n<10M
+extra_gated_fields:
+  Affiliation: text
+  Country: country
+  I want to use this model for:
+    type: select
+    options:
+    - Research
+    - Commercial
+    - label: Other
+      value: other
+  Job title:
+    type: select
+    options:
+    - Student
+    - Research graduate
+    - AI researcher
+    - AI developer/engineer
+    - Cybersecurity researcher
+    - Reporter
+    - Other
+  geo: ip_location
+library_name: transformers
+---
+
+# PRIMUS: A Pioneering Collection of Open-Source Datasets for Cybersecurity LLM Training
+
+## 🤗 Primus-FineWeb
+
+The **Primus-FineWeb** dataset is constructed by filtering cybersecurity-related text from FineWeb, a refined version of Common Crawl. We began by leveraging _Primus-Seed_, a high-quality dataset of manually curated cybersecurity text, as positive samples. We then sampled ten times the amount of data from FineWeb as negative samples and trained a **binary cybersecurity classifier** based on TinyBERT. Using this classifier, we assigned each text in FineWeb a score between **0 and 1** and filtered out texts with a score greater than **0.003**, creating the Primus-FineWeb with 15.3 billion tokens. However, after discovering a significant amount of duplicate content, we performed deduplication, reducing the final dataset to **🔥 2.57 billion tokens of cybersecurity corpus**.
+
+🚀🚀 For more details, see our paper:  
+[https://arxiv.org/abs/2502.11191](https://arxiv.org/abs/2502.11191)
+
+---
+
+## Why was the threshold set at 0.003?
+
+We divided the score range (0-1) into several bins and randomly sampled 50 examples from each bin. These samples were then scored by GPT-4o to determine the proportion of text that was "_truly_" cybersecurity-related. We found that if the score was below 0.003, the proportion of cybersecurity text fell below 50%.
+
+<img src="https://i.imgur.com/XbqpmbI.png" alt="Threshold Selection" width="60%">
+
+
+## FineWeb: Cybersecurity Score vs. Token Count
+
+<img src="https://i.imgur.com/6twJL1p.png" alt="Cybersecurity Score vs. Token Count" width="65%">
+
+---
+
+## License
+
+This dataset is released under the **ODC-By** license. However, you must still comply with the **FineWeb license** and the **Common Crawl Terms of Use**.