datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
dolma3_mix-6T-1025-7B
⚠️ WARNING: This dataset is intended ONLY for reproducing Olmo 3 7B ⚠️
For all other training use cases, including training from scratch, please utilize our primary dolma 3 data mix: https://huggingface.co/datasets/allenai/dolma3_mix-6T.
Note: Some olmOCR science PDFs in the current dataset have been redacted following the training of Olmo 3 7B. These texts are indicated with [REMOVED] in the text field. This will affect reproducibility of Olmo 3 7B.
For this reason, please use… See the full description on the dataset page: https://huggingface.co/datasets/allenai/dolma3_mix-6T-1025-7B.Eurus-2-7B-SFT_eval_2e29
mlfoundations-dev/Eurus-2-7B-SFT_eval_2e29
Precomputed model outputs for evaluation.
Evaluation Results
Summary
Metric
AIME24
AMC23
MATH500
MMLUPro
JEEBench
GPQADiamond
LiveCodeBench
CodeElo
CodeForces
AIME25
HLE
LiveCodeBenchv5
Accuracy
2.3
21.0
30.6
11.0
11.4
10.4
6.8
1.5
2.1
1.3
4.1
4.4
AIME24
Average Accuracy: 2.33% ± 0.67%
Number of Runs: 10
Run
Accuracy
Questions Solved
Total Questions
1
0.00%
0
30
2
3.33%
1… See the full description on the dataset page: https://huggingface.co/datasets/mlfoundations-dev/Eurus-2-7B-SFT_eval_2e29.details_CohereForAI__c4ai-command-r7b-arabic-02-2025_v2
Dataset Card for Evaluation run of CohereForAI/c4ai-command-r7b-arabic-02-2025
Dataset automatically created during the evaluation run of model CohereForAI/c4ai-command-r7b-arabic-02-2025.
The dataset is composed of 116 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 4 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing… See the full description on the dataset page: https://huggingface.co/datasets/OALL/details_CohereForAI__c4ai-command-r7b-arabic-02-2025_v2.Dolci-Think-SFT-7B
Dolci-Think-SFT
Sources include a mixture of existing reasoning traces:
OpenThoughts 3 (Apache 2.0): Extended to 32K context length and downsampled code prompts to 16X multiple, to 941,166 total prompts. Access our version, Dolci OpenThoughts 3 here.
SYNTHETIC-2 (Apache 2.0) via the SFT-Verified split, 104,569 prompts.
Nemotron Post-training dataset (CC BY 4), code split only, 113,777 prompts.
New prompts and new reasoning traces from us (all ODC-BY-1.0):
Dolci Think Persona… See the full description on the dataset page: https://huggingface.co/datasets/allenai/Dolci-Think-SFT-7B.llama2_7b_chat-boolq-results
Dataset Card for "llama2_7b_chat-boolq-results"
More Information needed
DeepSeek-R1-Distill-Qwen-7B_eval_d81a
mlfoundations-dev/DeepSeek-R1-Distill-Qwen-7B_eval_d81a
Precomputed model outputs for evaluation.
Evaluation Results
Summary
Metric
MMLUPro
HMMT
HLE
AIME25
LiveCodeBenchv5
Accuracy
43.4
25.0
12.4
36.0
34.5
MMLUPro
Accuracy: 43.38%
Accuracy
Questions Solved
Total Questions
43.38%
N/A
N/A
HMMT
Average Accuracy: 25.00% ± 1.72%
Number of Runs: 10
Run
Accuracy
Questions Solved
Total Questions
1… See the full description on the dataset page: https://huggingface.co/datasets/mlfoundations-dev/DeepSeek-R1-Distill-Qwen-7B_eval_d81a.llama2_7b_chat-piqa-resultsrollouts-olmo7b-cue-search
rollouts-olmo7b-cue-search
Model: allenai/Olmo-3-1025-7B (snapshot a81bae42).
Tokenizer: allenai/Olmo-3-1025-7B (snapshot a81bae42).
Protocol: RL-Zero prompt, MATH-500 x 4 rollouts, budget 31,744, T 0.6, top-p 0.95, seed 20260819 (depth-2 exhaustive and n-gram chain: seed 20260821); the top-20 beam nominee screen, ten random-opener arms, every depth-2 opener (84 shards, arm names unique across shards) and the n-gram chain arms.
Rollouts generated on the CSAIL cluster for the… See the full description on the dataset page: https://huggingface.co/datasets/reasoning-cues/rollouts-olmo7b-cue-search.wenetspeech_small_7B_v2details_Lansechen__Qwen2.5-7B-Open-R1-GRPO-math-lighteval
Dataset Card for Evaluation run of Lansechen/Qwen2.5-7B-Open-R1-GRPO-math-lighteval
Dataset automatically created during the evaluation run of model Lansechen/Qwen2.5-7B-Open-R1-GRPO-math-lighteval.
The dataset is composed of 5 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 23 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always… See the full description on the dataset page: https://huggingface.co/datasets/Lansechen/details_Lansechen__Qwen2.5-7B-Open-R1-GRPO-math-lighteval.lm-eval-results-AurelPx-Pegasus-7b-slerp-private
Dataset Card for Evaluation run of AurelPx/Pegasus-7b-slerp
Dataset automatically created during the evaluation run of model AurelPx/Pegasus-7b-slerp
The dataset is composed of 62 configuration(s), each one corresponding to one of the evaluated task.
The dataset has been created from 6 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results.
An… See the full description on the dataset page: https://huggingface.co/datasets/nyu-dice-lab/lm-eval-results-AurelPx-Pegasus-7b-slerp-private.Dolci-Think-SFT-7B-multiturnDeepSeek-R1-Distill-Qwen-7B_eval_03-07-25_17-55_0981
mlfoundations-dev/DeepSeek-R1-Distill-Qwen-7B_eval_03-07-25_17-55_0981
Precomputed model outputs for evaluation.
Evaluation Results
Summary
Metric
AIME24
AIME25
AMC23
GPQADiamond
MATH500
Accuracy
42.7
22.7
67.0
33.3
79.6
AIME24
Average Accuracy: 42.67% ± 4.75%
Number of Runs: 5
Run
Accuracy
Questions Solved
Total Questions
1
50.00%
15
30
2
26.67%
8
30
3
53.33%
16
30
4
50.00%
15
30
5
33.33%
10
30… See the full description on the dataset page: https://huggingface.co/datasets/mlfoundations-dev/DeepSeek-R1-Distill-Qwen-7B_eval_03-07-25_17-55_0981.Taur_CoT_Analysis_Project___mistralai__Mistral-7B-Instruct-v0.3AA_preference_vicuna-7b_cosi_cutfineweb-edu-2013-qwen2-7b
FineWeb-Edu 2013 with Qwen2-7B token counts
Every 2013 FineWeb-Edu document, prepared for continued pretraining, with token
counts computed by a pinned Qwen2-7B tokenizer.
The pipeline is year-agnostic: the year, source revision, tokenizer contract,
and selection rule all come from a config file. 2013 uses
processing_config.json. The 2017 companion dataset, which is large enough to
require shuffling and a token budget rather than retaining everything, is at… See the full description on the dataset page: https://huggingface.co/datasets/stevenyuan666/fineweb-edu-2013-qwen2-7b.Dolci-Think-RL-7B
Dolci-Think-RL-7B
Dataset Summary
Dolci-Think-RL-7B is the reinforcement learning dataset used to train the Olmo-3-7B-Think model.It contains 102,014 prompts designed to elicit deep reasoning across:
Math
Coding
Precise Instruction Following
General Chat
It blends high-quality curated sources with filtering designed for deliberate reasoning.
Dataset Composition
Total Samples: 102,014
Original Dataset Contribution… See the full description on the dataset page: https://huggingface.co/datasets/allenai/Dolci-Think-RL-7B.details_MaziyarPanahi__calme-2.7-qwen2-7b
Dataset Card for Evaluation run of MaziyarPanahi/calme-2.7-qwen2-7b
Dataset automatically created during the evaluation run of model MaziyarPanahi/calme-2.7-qwen2-7b.
The dataset is composed of 136 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest… See the full description on the dataset page: https://huggingface.co/datasets/OALL/details_MaziyarPanahi__calme-2.7-qwen2-7b.lm-eval-results-shyamieee-Padma-SLM-7b-v1.0-private
Dataset Card for Evaluation run of shyamieee/Padma-SLM-7b-v1.0
Dataset automatically created during the evaluation run of model shyamieee/Padma-SLM-7b-v1.0
The dataset is composed of 62 configuration(s), each one corresponding to one of the evaluated task.
The dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results.
An… See the full description on the dataset page: https://huggingface.co/datasets/nyu-dice-lab/lm-eval-results-shyamieee-Padma-SLM-7b-v1.0-private.M4-encoded-falcon-7bAA_preference_vicuna-7b_l0_cutDolci-Think-SFT-7B-decontaminated
Decontamination
This dataset is a decontaminated version of allenai/Dolci-Think-SFT-7B.
Benchmarks used
MATH500: HuggingFaceH4/MATH-500 (subset=default, split=test)
AIME24: HuggingFaceH4/aime_2024 (subset=default, split=train)
AIME25: math-ai/aime25 (subset=default, split=test)
AMC23: math-ai/amc23 (subset=default, split=test)
JEEBench: daman1209arora/jeebench (subset=default, split=test)
GPQADiamond: Idavidrein/gpqa (subset=gpqa_diamond, split=train)… See the full description on the dataset page: https://huggingface.co/datasets/openeurollm/Dolci-Think-SFT-7B-decontaminated.AA_preference_vicuna-7b_cooccur_cutDolci-Think-DPO-7B
Dolci Think 7B DPO Mixture
This dataset is licensed under ODC-BY. It is intended for research and educational use in accordance with Ai2's Responsible Use Guidelines.
The Dolci Think 7B DPO mixture was used to preference tune Olmo 3 Think 7B. It contains 150,000 preference pairs created with the preference heuristic described in Delta Learning (Geng et al. 2025).
Citation
@misc{olmo2025olmo3,
title={Olmo 3},
author={Team Olmo and Allyson Ettinger and Amanda Bertsch… See the full description on the dataset page: https://huggingface.co/datasets/allenai/Dolci-Think-DPO-7B.DeepSeek-R1-Distill-Qwen-7B_eval_118b
mlfoundations-dev/DeepSeek-R1-Distill-Qwen-7B_eval_118b
Precomputed model outputs for evaluation.
Evaluation Results
LiveCodeBenchv5_official
Average Accuracy: 31.18% ± nan%
Number of Runs: 1
Run
Accuracy
Questions Solved
Total Questions
1
31.18%
87
279
AA_preference_vicuna-7b_cooccur_fullaime_1983_2023_deepseek-r1-distill-qwen-7b_traces_32768dolci_think_rl_7b_messages_hybrid_275mQwen2.5-7B-Instruct_qwq_mix_r1_science_eval_8179
mlfoundations-dev/Qwen2.5-7B-Instruct_qwq_mix_r1_science_eval_8179
Precomputed model outputs for evaluation.
Evaluation Results
Summary
Metric
AIME24
AMC23
MATH500
JEEBench
GPQADiamond
LiveCodeBench
CodeElo
CodeForces
AIME25
HLE
LiveCodeBenchv5
HMMT
Accuracy
60.7
90.8
89.4
63.2
52.4
48.5
27.4
26.2
48.3
12.0
34.3
34.7
AIME24
Average Accuracy: 60.67% ± 2.25%
Number of Runs: 10
Run
Accuracy
Questions Solved
Total Questions… See the full description on the dataset page: https://huggingface.co/datasets/mlfoundations-dev/Qwen2.5-7B-Instruct_qwq_mix_r1_science_eval_8179.llama2_7b_chat-siqa-results