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Stage 1 (S1): General Knowledge Anchor — 6M FineWeb-Edu-Dedup
1. Project Overview
This dataset represents the General Knowledge Acquisition Phase (S1) for a research project focused on developing a Domain-Adaptive LLM for ISO 27001 Information Security Auditing.
S1 serves as the cognitive foundation. This corpus is designed to establish high-level linguistic proficiency and general reasoning before the introduction of specialized regulatory standards in Stage 2.
2. Dataset Summary
- Total Samples: 6,000,000
- Primary Source: HuggingFaceTB/smollm-corpus
- Role: General Reasoning & Scientific Logic Base.
3. Sourcing & Preprocessing (S1 Methodology)
The sourcing logic for this 6M slice prioritized Knowledge Density over raw volume:
- Educational Filtering: Only samples with a high "educational score" (classifier-based) were retained to ensure the model learns professional and structured language.
- Sharding: Organized into 120 Parquet shards to support high-throughput, multi-node training.
4. Technical Specifications
| Parameter | Value |
|---|---|
| Format | Parquet (Compressed) |
| Average Sequence Length | 600 - 4096 tokens |
| Language | English (High-Proficiency) |
5. Usage in Continual Pre-training
This dataset is intended to be interleaved with Math/Code and Multilingual streams to reach a Stage 1 target of 10B tokens.
Loading for Training (Streaming)
from datasets import load_dataset
dataset = load_dataset("JoTeqtheFirstAI/fineweb-edu-dedup6m", split="train", streaming=True)
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