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dvilasuero/jailbreak-classification-reasoning-results

published by @dvilasuero

Alignment dataset tracked in the /datasets sub-catalog.

Lifetime downloads
358
Last 30 days
21
Likes
-
Size
315 KB
Created on HF
2025-03-10
Age
1 years ago

Description

Results Summary

Model

Accuracy

Total

Correct

Unparsable

qwq32

90.00%

100

90

4

r1

93.00%

100

93

3

llama70B

69.00%

100

69

18

Prediction Distribution

Model

Benign

Jailbreak

Unparsable

qwq32

44

52

4

r1

43

54

3

llama70B

50

32

18

Tags

size_categories:n<1Kformat:parquetmodality:textlibrary:datasetslibrary:pandaslibrary:mlcroissantlibrary:polarsregion:us

README current version from Hugging Face


dataset_info:
features:

  • name: prompt
    dtype: string
  • name: type
    dtype: string
  • name: qwq32
    dtype: string
  • name: r1
    dtype: string
  • name: llama70B
    dtype: string
  • name: qwq32_extracted
    dtype: string
  • name: r1_extracted
    dtype: string
  • name: llama70B_extracted
    dtype: string
    splits:
  • name: train
    num_bytes: 627875
    num_examples: 100
    download_size: 319424
    dataset_size: 627875
    configs:
  • config_name: default
    data_files:
    • split: train
      path: data/train-*

Results Summary

Model Accuracy Total Correct Unparsable
qwq32 90.00% 100 90 4
r1 93.00% 100 93 3
llama70B 69.00% 100 69 18

Prediction Distribution

Model Benign Jailbreak Unparsable
qwq32 44 52 4
r1 43 54 3
llama70B 50 32 18

README history 5 revisions

Every night we snapshot the README of every dataset in the catalog. When the SHA changes we archive the new version and diff it against the last. This is the evolving thought record of the alignment-data field: what the author decided to say about the corpus, and how that framing shifted over time.

  1. 2025-03-10Update README.md98ac1a6952 B
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  2. 2025-03-10Update README.mdc75a6e61.1 KB
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  3. 2025-03-10Upload dataset303a326539 B
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  4. 2025-03-10Upload dataset6800815535 B
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  5. 2025-03-10initial commit7ef767d0 B
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Repository

Download the dataset

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Copy any of these snippets into your notebook or terminal. All three fetch directly from Hugging Face using your own credentials.

Recommended: datasets library (Python)
from datasets import load_dataset
ds = load_dataset("dvilasuero/jailbreak-classification-reasoning-results")
Raw snapshot (Python)
from huggingface_hub import snapshot_download
snapshot_download(repo_id="dvilasuero/jailbreak-classification-reasoning-results", repo_type="dataset")
git clone (requires git-lfs)
git clone https://huggingface.co/datasets/dvilasuero/jailbreak-classification-reasoning-results
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