---
license: apache-2.0
task_categories:
- text-generation
- question-answering
language:
- en
tags:
- DCLM
- fineweb
- edu
- pretrain
- pretraining
- web
- reason
- reasoning
- dense
- fine
- fine data
- ultra
- pro
- DCLM Pro
- DCLM baseline
- thought
- thoughts
- think
- thinking
- post train
- posttrain
size_categories:
- 1M<n<10M
---
# DCLM Ultra

**DCLM Ultra** is an improved, deduplicated and filtered version of **DCLM Pro** (Filtered DCLM, 1.5% better compared to DCLM baseline).

It achieves **superior performance** across benchmarks including hellaswag and piqa, also achieving better loss compared to pro.

**3M model trained on only DCLM Pro vs only Ultra, same architecture, same training budget.**

| Metric | DCLM Pro | DCLM Ultra |
|---|---:|---:|
| Training loss | 3.37 | **3.27** |
| PIQA | 53.65% | **54.95%** |
| HellaSwag | 25.45% | **25.54%** |

## Dataset Details

- **Curated by:** AInion
- **Funded by:** ArrowAI
- **Shared by:** MoreThought
- **Language:** english
- **License:** apache 2.0

### Dataset Sources

- **Main Source:** https://huggingface.co/datasets/mlfoundations/dclm-baseline-1.0
- **Pro Source:** https://huggingface.co/datasets/mlfoundations/dclm-baseline-1.0-parquet
- **Pro Repo:** https://huggingface.co/datasets/gair-prox/DCLM-pro

## Uses

- PreTraining SLMs on clean, heavily filtered data.
- PostTraining LLMs on clean, heavily filtered data.
- PreTraining data quality benefits on SLMs research.