size_categories:1K<n<10K format:parquet modality:tabular modality:text library:datasets library:pandas library:mlcroissant library:polars library:distilabel region:us synthetic distilabel rlaif
---
size_categories: n<1K
dataset_info:
  features:
  - name: question_id
    dtype: int64
  - name: question
    dtype: string
  - name: options
    sequence: string
  - name: answer
    dtype: string
  - name: answer_index
    dtype: int64
  - name: cot_content
    dtype: string
  - name: category
    dtype: string
  - name: src
    dtype: string
  - name: instruction
    dtype: string
  - name: thinking
    dtype: string
  - name: output
    dtype: string
  - name: distilabel_metadata
    struct:
    - name: raw_input_text_generation_with_cot_reflection_0
      list:
      - name: content
        dtype: string
      - name: role
        dtype: string
    - name: raw_output_text_generation_with_cot_reflection_0
      dtype: string
  - name: model_name
    dtype: string
  splits:
  - name: train
    num_bytes: 8540542
    num_examples: 1000
  download_size: 2946372
  dataset_size: 8540542
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
tags:
- synthetic
- distilabel
- rlaif
---

<p align="left">
  <a href="https://github.com/argilla-io/distilabel">
    <img src="https://raw.githubusercontent.com/argilla-io/distilabel/main/docs/assets/distilabel-badge-light.png" alt="Built with Distilabel" width="200" height="32"/>
  </a>
</p>

# Dataset Card for meta-llama_Llama-3.1-70B-Instruct_cot_mmlu-pro_20241017_101055

This dataset has been created with [distilabel](https://distilabel.argilla.io/).



## Dataset Summary

This dataset contains a `pipeline.yaml` which can be used to reproduce the pipeline that generated it in distilabel using the `distilabel` CLI:

```console
distilabel pipeline run --config "https://huggingface.co/datasets/dvilasuero/meta-llama_Llama-3.1-70B-Instruct_cot_mmlu-pro_20241017_101055/raw/main/pipeline.yaml"
```

or explore the configuration:

```console
distilabel pipeline info --config "https://huggingface.co/datasets/dvilasuero/meta-llama_Llama-3.1-70B-Instruct_cot_mmlu-pro_20241017_101055/raw/main/pipeline.yaml"
```

## Dataset structure

The examples have the following structure per configuration:


<details><summary> Configuration: default </summary><hr>

```json
{
    "answer": "I",
    "answer_index": 8,
    "category": "business",
    "cot_content": "",
    "distilabel_metadata": {
        "raw_input_text_generation_with_cot_reflection_0": [
            {
                "content": "You are a helpful AI assistant",
                "role": "system"
            },
            {
                "content": "You are an AI assistant that uses a Chain of Thought (CoT) approach with reflection to answer queries. You MUST STRICTLY follow these steps and format:\n\n1. Think through the problem step by step within ONE pair of \u003cthinking\u003e tags.\n2. Include one or more reflections on your thinking within \u003creflection\u003e tags inside the \u003cthinking\u003e section. This reflections must verify and be critical about previous thinking steps, not just common sense or cliche reflections. Only add reflections that are useful to verify and make sure the final output is correct.\n3. Make any necessary adjustments based on your reflections, still within the \u003cthinking\u003e tags.\n4. Verify your answer against common knowledge or basic facts relevant to the question type.\n5. Provide your final, concise answer within the \u003coutput\u003e tags.\n\nCRITICAL: \n- Use EXACTLY ONE pair of \u003cthinking\u003e tags.\n- Include AT LEAST ONE pair of \u003creflection\u003e tags INSIDE the \u003cthinking\u003e section.\n- ALWAYS include a verification step before your final answer.\n- Put your FINAL ANSWER ONLY inside the \u003coutput\u003e tags.\n- ALWAYS include both opening \u003coutput\u003e and closing \u003c/output\u003e tags.\n\nHere\u0027s the EXACT format you MUST follow:\n\n\u003cthinking\u003e\n[Your step-by-step reasoning goes here. This is your internal thought process, not the final answer.]\n\u003creflection\u003e\n[Your first reflection on your reasoning, checking for errors or improvements]\n\u003c/reflection\u003e\n[Any adjustments based on your first reflection]\n\u003creflection\u003e\n[Your second reflection, if needed]\n\u003c/reflection\u003e\n[Any further adjustments]\n\u003creflection\u003e\n[More verifications against common knowledge, basic facts, your thought process, all depending on the type of user query, don\u0027t overthink simple questions]\n\u003c/reflection\u003e\n[Final confirmation or any last adjustments based on verification]\n\u003c/thinking\u003e\n\u003coutput\u003e\n[Your final, concise answer to the query. This is the ONLY part that will be shown to the user.]\n\u003c/output\u003e\n\n\nFailure to follow this EXACT format, including the verification step, will result in incorrect processing of your response. Always double-check your reasoning and facts against well-established knowledge in the relevant field, whether it\u0027s mathematics, science, history, or any other domain. Verify your answer using multiple approaches when possible, and be prepared to correct any initial misconceptions.\nUser query: The following is a multiple choice question. Think step by step and then finish your answer with \"the answer is (X)\" where X is the correct letter choice.\nQuestion:\nThe Century Shoe Company bought a machine for $1200. Depreciation was charged at the rate of 20% of the declining balance. Find the book value at the end of 3 years.\nOptions:\nA. $840.00\nB. $729.60\nC. $512.00\nD. $691.20\nE. $768.00\nF. $900.00\nG. $960.00\nH. $585.60\nI. $614.40\nJ. $450.00\nAnswer: Let\u0027s think step by step.",
                "role": "user"
            }
        ],
        "raw_output_text_generation_with_cot_reflection_0": "\u003cthinking\u003e\nTo find the book value at the end of 3 years, we need to calculate the depreciation for each year and subtract it from the initial cost. Depreciation is charged at the rate of 20% of the declining balance.\n\nYear 1:\nInitial cost = $1200\nDepreciation = 20% of $1200 = 0.20 * $1200 = $240\nBook value at the end of Year 1 = $1200 - $240 = $960\n\nYear 2:\nDepreciation = 20% of $960 = 0.20 * $960 = $192\nBook value at the end of Year 2 = $960 - $192 = $768\n\nYear 3:\nDepreciation = 20% of $768 = 0.20 * $768 = $153.60\nBook value at the end of Year 3 = $768 - $153.60 = $614.40\n\n\u003creflection\u003e\nWe need to check if we have calculated the depreciation correctly. Let\u0027s verify the calculation for each year. The depreciation for Year 1 is 20% of $1200, which is correct. For Year 2, the depreciation is 20% of the book value at the end of Year 1, which is $960. For Year 3, the depreciation is 20% of the book value at the end of Year 2, which is $768. The calculations seem to be correct.\n\u003c/reflection\u003e\n\nWe can also verify our answer by checking if the book value at the end of 3 years is less than the book value at the end of 2 years, which is the case. \n\n\u003creflection\u003e\nAnother way to verify our answer is to check if we can find the same result using a different approach. We can calculate the total depreciation over 3 years and subtract it from the initial cost. Total depreciation = $240 + $192 + $153.60 = $585.60. Book value at the end of 3 years = $1200 - $585.60 = $614.40. This confirms our previous answer.\n\u003c/reflection\u003e\n\n\u003c/thinking\u003e\n\u003coutput\u003e\nThe answer is I.\n\u003c/output\u003e"
    },
    "instruction": "The following is a multiple choice question. Think step by step and then finish your answer with \"the answer is (X)\" where X is the correct letter choice.\nQuestion:\nThe Century Shoe Company bought a machine for $1200. Depreciation was charged at the rate of 20% of the declining balance. Find the book value at the end of 3 years.\nOptions:\nA. $840.00\nB. $729.60\nC. $512.00\nD. $691.20\nE. $768.00\nF. $900.00\nG. $960.00\nH. $585.60\nI. $614.40\nJ. $450.00\nAnswer: Let\u0027s think step by step.",
    "model_name": "meta-llama/Llama-3.1-70B-Instruct",
    "options": [
        "$840.00",
        "$729.60",
        "$512.00",
        "$691.20",
        "$768.00",
        "$900.00",
        "$960.00",
        "$585.60",
        "$614.40",
        "$450.00"
    ],
    "output": "The answer is I.",
    "question": "The Century Shoe Company bought a machine for $1200. Depreciation was charged at the rate of 20% of the declining balance. Find the book value at the end of 3 years.",
    "question_id": 853,
    "src": "stemez-Business",
    "thinking": "To find the book value at the end of 3 years, we need to calculate the depreciation for each year and subtract it from the initial cost. Depreciation is charged at the rate of 20% of the declining balance.\n\nYear 1:\nInitial cost = $1200\nDepreciation = 20% of $1200 = 0.20 * $1200 = $240\nBook value at the end of Year 1 = $1200 - $240 = $960\n\nYear 2:\nDepreciation = 20% of $960 = 0.20 * $960 = $192\nBook value at the end of Year 2 = $960 - $192 = $768\n\nYear 3:\nDepreciation = 20% of $768 = 0.20 * $768 = $153.60\nBook value at the end of Year 3 = $768 - $153.60 = $614.40\n\n\u003creflection\u003e\nWe need to check if we have calculated the depreciation correctly. Let\u0027s verify the calculation for each year. The depreciation for Year 1 is 20% of $1200, which is correct. For Year 2, the depreciation is 20% of the book value at the end of Year 1, which is $960. For Year 3, the depreciation is 20% of the book value at the end of Year 2, which is $768. The calculations seem to be correct.\n\u003c/reflection\u003e\n\nWe can also verify our answer by checking if the book value at the end of 3 years is less than the book value at the end of 2 years, which is the case. \n\n\u003creflection\u003e\nAnother way to verify our answer is to check if we can find the same result using a different approach. We can calculate the total depreciation over 3 years and subtract it from the initial cost. Total depreciation = $240 + $192 + $153.60 = $585.60. Book value at the end of 3 years = $1200 - $585.60 = $614.40. This confirms our previous answer.\n\u003c/reflection\u003e"
}
```

This subset can be loaded as:

```python
from datasets import load_dataset

ds = load_dataset("dvilasuero/meta-llama_Llama-3.1-70B-Instruct_cot_mmlu-pro_20241017_101055", "default")
```

Or simply as it follows, since there's only one configuration and is named `default`: 

```python
from datasets import load_dataset

ds = load_dataset("dvilasuero/meta-llama_Llama-3.1-70B-Instruct_cot_mmlu-pro_20241017_101055")
```


</details>




