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---
license: cc-by-4.0
language:
- tr
size_categories:
- 10M<n<100M
task_categories:
- text-generation
tags:
- pretraining
- turkish
- deduplication
- quality-filtered
configs:
- config_name: minhash_deduped
data_files:
- split: train
path: "minhash_deduped/**/*.parquet"
- config_name: quality_filtered
data_files:
- split: train
path: "quality_filtered/**/*.parquet"
- config_name: consensus
data_files:
- split: train
path: "consensus/*.parquet"
---
# TurMix: Turkish Pretraining Data Mix
A high-quality Turkish pretraining dataset created by combining, filtering, and deduplicating multiple sources.
## Dataset Description
This dataset contains Turkish text from multiple web crawl sources, processed through a quality filtering and MinHash deduplication pipeline.
### Sources
- **C4** (mC4 Turkish subset)
- **CulturaX** (Turkish)
- **Fineweb-2** (tur_Latn)
- **HPLT-2** (tur_Latn, 5 shards)
- **VNGRS Web Corpus**
## Subsets
### 1. `minhash_deduped` (Recommended)
MinHash-deduplicated data. Each source was deduplicated individually to remove near-duplicate documents.
```python
from datasets import load_dataset
ds = load_dataset("AdaMLLab/TurMix", "minhash_deduped")
```
**Statistics:**
- ~27M documents
- 359GB compressed
### 2. `quality_filtered`
Quality-filtered data before deduplication. Use this if you want to apply your own deduplication.
```python
from datasets import load_dataset
ds = load_dataset("AdaMLLab/TurMix", "quality_filtered")
```
**Statistics:**
- ~49M documents
- 658GB compressed
### 3. `consensus`
Documents that appear in 2+ sources (exact text match). These are high-confidence documents verified across multiple crawls.
```python
from datasets import load_dataset
ds = load_dataset("AdaMLLab/TurMix", "consensus")
```
**Statistics:**
- 7.84M documents
- 13GB compressed
**Schema:**
- `text`: Document text
- `id`: Primary document ID
- `sources`: List of sources where document appears (e.g., `["c4", "culturax"]`)
- `all_ids`: All document IDs from all sources
- `metadata`: Additional metadata
## Quality Filtering
Documents were filtered based on:
- Language identification (Turkish Latin script ratio)
- Document length constraints
- Line quality metrics
- Repetition detection (including Turkish-specific patterns)
- Boilerplate/policy phrase removal
Filter thresholds based on Fineweb-2 Turkish configuration. |