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## Dataset Card: CoT-Collection
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This dataset encompasses a variety of tasks aimed at necessitating reasoning and diverse Chain-of-Thought strategies. While some tasks are intentionally simple and require minimal reasoning, others are more complex.
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*Note* that Big Bench Hard includes 27 different tasks.
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*Also Note* that the test set has a significantly different task distribution compared to the training set.
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The dataset includes GPQA, which should not be published in plain text online.
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Designed for reinforcement learning, this dataset lacks Chain-of-Thought annotations for the problems. It only provides questions and answers. However, a subset with automated Chain-of-Thought annotations is available here: [jeggers/CoT-Collection-Rationales](https://huggingface.co/datasets/jeggers/CoT-Collection-Rationales).
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The dataset consists of short questions, each with a maximum of 200 tokens for the question and correct answer (using the llama-2 tokenizer).
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This dataset is divided into four splits:
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- `train`: The training set.
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- `test_in_dist`: The test set with the same task distribution as the training set.
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- `finetune`: Intended for finetuning, with the same distribution as `train`.
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- `test_out_dist`: The test set with a different task distribution than the training set.
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The Code used to create this dataset can be found here: [dataset-builder](https://github.com/Jorineg/dataset-builder).
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### Statistics for the training set (62000 samples)
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![train_dataset](train_dataset.png)
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| Dataset | Proportion | Absolute | Random correct accuracy |
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|:-------------------------------|:-------------|:-----------|:--------------------------|
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| **Total** | **100.00%** | **61972** | **19.23%** |
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| big bench hard | 6.65% | 4123 | 15.82% |
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| MathQA | 5.44% | 3369 | 22.25% |
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| MATH | 5.43% | 3368 | 4.29% |
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| crosswords | 5.43% | 3368 | 0.12% |
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| ape210k | 5.43% | 3368 | 2.08% |
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| MMLU-Pro | 5.43% | 3368 | 11.68% |
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| DMath | 5.43% | 3368 | 4.12% |
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| SuperGLUE rte | 2.71% | 1682 | 50.16% |
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| SuperGLUE wic | 2.71% | 1682 | 50.00% |
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| SuperGLUE boolq | 2.71% | 1682 | 62.31% |
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| strategy-qa | 2.71% | 1681 | 53.23% |
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| ARC challenge | 2.71% | 1681 | 25.79% |
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| jeopardy | 2.71% | 1681 | 0.11% |
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| hellaswag | 2.71% | 1681 | 25.06% |
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| winogrande | 2.71% | 1681 | 50.01% |
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| riddle sense | 2.71% | 1681 | 20.64% |
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| com2sense | 2.71% | 1681 | 50.00% |
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| ANLI | 2.71% | 1681 | 40.51% |
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| reverse words | 2.71% | 1681 | 0.01% |
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| ARC easy | 2.71% | 1681 | 24.86% |
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| drop single number | 2.71% | 1681 | 12.50% |
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| logiqa2 | 2.71% | 1681 | 26.70% |
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| hotpot qa hard | 2.71% | 1681 | 3.24% |
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| asdiv | 2.58% | 1598 | 3.78% |
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| reversal curse | 1.89% | 1172 | 0.26% |
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| count chars in scrambled words | 1.35% | 838 | 16.68% |
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| count words in paragraph | 1.35% | 838 | 2.08% |
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| count chars in paragraph | 1.35% | 838 | 0.96% |
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| count chars in english words | 1.35% | 838 | 16.68% |
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| reclor | 1.35% | 834 | 25.28% |
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| svamp | 1.25% | 774 | 7.70% |
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| AIME | 1.06% | 654 | 0.96% |
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| truthful qa | 1.01% | 624 | 22.40% |
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| SuperGLUE WSC | 0.69% | 429 | 53.25% |
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| LSAT-LR | 0.53% | 327 | 21.35% |
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| SuperGLUE copa | 0.50% | 309 | 51.25% |
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| SAT Analogies | 0.47% | 289 | 24.40% |
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| SuperGLUE cb | 0.28% | 172 | 47.60% |
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| LSAT-AR | 0.23% | 142 | 20.53% |
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| RACE high school | 0.10% | 62 | 27.02% |
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| SuperGLUE multirc | 0.00% | 3 | 55.86% |
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### Statistics for the out of distribution test set (2731 samples)
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![test_dataset](test_dataset.png)
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| Dataset | Proportion | Absolute | Random correct accuracy |
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|:-------------------|:-------------|:-----------|:--------------------------|
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| **Total** | **100.00%** | **2731** | **14.00%** |
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| gsm8k | 36.58% | 999 | 3.20% |
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| last letter concat | 18.31% | 500 | 0.60% |
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| codah | 18.31% | 500 | 26.80% |
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| coin flip | 9.15% | 250 | 52.40% |
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| AIW | 7.32% | 200 | 22.00% |
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| AIW+ | 7.03% | 192 | 6.25% |
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| gpqa diamond | 3.30% | 90 | 29.29% | |