Datasets:
Tasks:
Text Generation
Modalities:
Text
Formats:
parquet
Languages:
English
Size:
10M - 100M
ArXiv:
License:
Fix the typo
Browse files
README.md
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@@ -317,7 +317,7 @@ Existing cybersecurity solutions often rely on proprietary APIs or lack domain a
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### Data Processing & Filtering
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1. **Classifier Training:** A binary classifier based on **ModernBERT-base** was trained on the "Cybersecurity Topic Classification" dataset (sourced from Reddit, StackExchange, and arXiv). It achieved 97.3% accuracy on validation.
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2. **Filtering:** This classifier was applied to FineWeb, identifying ~125M cybersecurity-relevant documents (~89.8B tokens).
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3. **General Knowledge Replay:** To avoid catastrophic forgetting, the cybersecurity data was mixed with FineWeb-Edu samples at a **30% replay ratio**.
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4. **Deduplication:** Global deduplication was performed using MinHash-LSH (via DataTrove), reducing the corpus size by ~47.9% in tokens.
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5. **Chunking:** The final dataset comprises the latest 5 chronological chunks from the processed data to manage computational costs.
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| 317 |
### Data Processing & Filtering
|
| 318 |
|
| 319 |
1. **Classifier Training:** A binary classifier based on **ModernBERT-base** was trained on the "Cybersecurity Topic Classification" dataset (sourced from Reddit, StackExchange, and arXiv). It achieved 97.3% accuracy on validation.
|
| 320 |
+
2. **Filtering:** This classifier was applied to FineWeb, identifying \~125M cybersecurity-relevant documents (\~89.8B tokens).
|
| 321 |
3. **General Knowledge Replay:** To avoid catastrophic forgetting, the cybersecurity data was mixed with FineWeb-Edu samples at a **30% replay ratio**.
|
| 322 |
4. **Deduplication:** Global deduplication was performed using MinHash-LSH (via DataTrove), reducing the corpus size by ~47.9% in tokens.
|
| 323 |
5. **Chunking:** The final dataset comprises the latest 5 chronological chunks from the processed data to manage computational costs.
|