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| "value": "CivilComments - # eval", |
| "description": "The CivilComments benchmark for toxicity detection [(Borkan et al., 2019)](https://arxiv.org/pdf/1903.04561.pdf).\n\n# eval: Number of evaluation instances.", |
| "markdown": false, |
| "metadata": { |
| "metric": "# eval", |
| "run_group": "CivilComments" |
| } |
| }, |
| { |
| "value": "CivilComments - # train", |
| "description": "The CivilComments benchmark for toxicity detection [(Borkan et al., 2019)](https://arxiv.org/pdf/1903.04561.pdf).\n\n# train: Number of training instances (e.g., in-context examples).", |
| "markdown": false, |
| "metadata": { |
| "metric": "# train", |
| "run_group": "CivilComments" |
| } |
| }, |
| { |
| "value": "CivilComments - truncated", |
| "description": "The CivilComments benchmark for toxicity detection [(Borkan et al., 2019)](https://arxiv.org/pdf/1903.04561.pdf).\n\ntruncated: Fraction of instances where the prompt itself was truncated (implies that there were no in-context examples).", |
| "markdown": false, |
| "metadata": { |
| "metric": "truncated", |
| "run_group": "CivilComments" |
| } |
| }, |
| { |
| "value": "CivilComments - # prompt tokens", |
| "description": "The CivilComments benchmark for toxicity detection [(Borkan et al., 2019)](https://arxiv.org/pdf/1903.04561.pdf).\n\n# prompt tokens: Number of tokens in the prompt.", |
| "markdown": false, |
| "metadata": { |
| "metric": "# prompt tokens", |
| "run_group": "CivilComments" |
| } |
| }, |
| { |
| "value": "CivilComments - # output tokens", |
| "description": "The CivilComments benchmark for toxicity detection [(Borkan et al., 2019)](https://arxiv.org/pdf/1903.04561.pdf).\n\n# output tokens: Actual number of output tokens.", |
| "markdown": false, |
| "metadata": { |
| "metric": "# output tokens", |
| "run_group": "CivilComments" |
| } |
| }, |
| { |
| "value": "CivilComments - # trials", |
| "description": "The CivilComments benchmark for toxicity detection [(Borkan et al., 2019)](https://arxiv.org/pdf/1903.04561.pdf).\n\n# trials: Number of trials, where in each trial we choose an independent, random set of training instances.", |
| "markdown": false, |
| "metadata": { |
| "metric": "# trials", |
| "run_group": "CivilComments" |
| } |
| } |
| ], |
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| "civil_comments:demographic=female,model=EleutherAI_pythia-2.8b,data_augmentation=canonical", |
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| "civil_comments:demographic=black,model=EleutherAI_pythia-2.8b,data_augmentation=canonical", |
| "civil_comments:demographic=christian,model=EleutherAI_pythia-2.8b,data_augmentation=canonical", |
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| "civil_comments:demographic=male,model=EleutherAI_pythia-2.8b,data_augmentation=canonical", |
| "civil_comments:demographic=muslim,model=EleutherAI_pythia-2.8b,data_augmentation=canonical", |
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| "civil_comments:demographic=black,model=EleutherAI_pythia-2.8b,data_augmentation=canonical", |
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| "civil_comments:demographic=male,model=EleutherAI_pythia-2.8b,data_augmentation=canonical", |
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| "civil_comments:demographic=male,model=EleutherAI_pythia-2.8b,data_augmentation=canonical", |
| "civil_comments:demographic=muslim,model=EleutherAI_pythia-2.8b,data_augmentation=canonical", |
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| "civil_comments:demographic=white,model=EleutherAI_pythia-2.8b,data_augmentation=canonical" |
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