metadata

license: mit
dataset_info:
  features:
    - name: id
      dtype: int64
    - name: conversation
      list:
        - name: content
          dtype: string
        - name: role
          dtype: string
    - name: token_count
      dtype: int64
    - name: turns_count
      dtype: int64
    - name: markdown_conversation
      list:
        - name: content
          dtype: string
        - name: role
          dtype: string
    - name: source
      dtype: string
    - name: topic
      dtype: string
    - name: safety_flags
      sequence: string
  splits:
    - name: train
      num_bytes: 374660
      num_examples: 201
  download_size: 172981
  dataset_size: 374660
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*

BoDmagh dataset 🧠

The BoDmagh dataset is a Supervised Fine-Tuning (SFT) dataset for the Darija language. I created it manually, ensuring high quality. The dataset is in JSON format and includes conversations between a user and an assistant.

I update the dataset daily, so make sure to check the repository regularly.

Time spent

Creating this dataset has been a labor of love. I’ve dedicated approximately 14 hours and 40 minutes so far, manually curating each entry to ensure high quality. I continue to add new entries daily, so this number will keep growing.

Content

1. Structure

The dataset is a JSON file containing a list of objects. Each object represents a single conversation entry and includes several metadata fields along with the conversation itself.

Here are the main fields within each conversation object:

id: A unique integer identifier for the conversation.
conversation: A list of message objects representing the turns in the conversation. Each message object has:
- role: Either user or assistant.
- content: The text content of the message turn (plain text).
token_count: The total number of tokens in the conversation field, calculated using the darija tokenizer.
turns_count: The total number of turns (messages) in the conversation.
markdown_conversation: A list of message objects similar to conversation, but the content may include Markdown formatting (e.g., bolding, lists) where applicable.
source: Indicates how the conversation was generated (e.g., "Manually generated").
topic: A label indicating the primary topic of the conversation (e.g., "Science", "Travel", "Chit-chat/Games/Humor").
safety_flags: A list of strings indicating any safety concerns identified in the conversation (e.g., ["harmful_content_request", "refusal"]). An empty list [] means the conversation is considered safe.

Note: The system message is not included, but you can add it if needed for your specific fine-tuning format.

Here is an example of a single conversation object:

{
    "id": 74,
    "conversation": [
        {
            "role": "user",
            "content": "شحال بعيدة علينا الشمس؟"
        },
        {
            "role": "assistant",
            "content": "الشمس بعيدة علينا ب 150 مليون كيلومتر تقريبا."
        },
        {
            "role": "user",
            "content": "ويلي ويلي شحال بعيداااا."
        },
        {
            "role": "assistant",
            "content": "واييه راه هاد الكون كبير بزاف صعيب الواحد يتخيل الكبورية ديالو."
        },
        {
            "role": "user",
            "content": "شناهية سنة ضوئية؟"
        },
        {
            "role": "assistant",
            "content": "هي المسافة اللي الضو كيضربها فعام."
        },
        {
            "role": "user",
            "content": "شحال فيها من كيلومتر؟"
        },
        {
            "role": "assistant",
            "content": "سنة ضوئية فيها 9.461 تريليون كيلومتر."
        },
        {
            "role": "user",
            "content": "والله اتا بزاف هاد الكون."
        },
        {
            "role": "assistant",
            "content": "الى عندك شي سؤال خور غولهالي."
        }
    ],
    "token_count": 97,
    "turns_count": 10,
    "markdown_conversation": [
        {
            "role": "user",
            "content": "شحال بعيدة علينا الشمس؟"
        },
        {
            "role": "assistant",
            "content": "الشمس بعيدة علينا ب **150 مليون كيلومتر** تقريبا."
        },
        {
            "role": "user",
            "content": "ويلي ويلي شحال بعيداااا."
        },
        {
            "role": "assistant",
            "content": "واييه راه هاد الكون كبير بزاف صعيب الواحد يتخيل الكبورية ديالو."
        },
        {
            "role": "user",
            "content": "شناهية سنة ضوئية؟"
        },
        {
            "role": "assistant",
            "content": "هي المسافة اللي الضو كيضربها فعام."
        },
        {
            "role": "user",
            "content": "شحال فيها من كيلومتر؟"
        },
        {
            "role": "assistant",
            "content": "سنة ضوئية فيها **9.461 تريليون كيلومتر**."
        },
        {
            "role": "user",
            "content": "والله اتا بزاف هاد الكون."
        },
        {
            "role": "assistant",
            "content": "الى عندك شي سؤال خور غولهالي."
        }
    ],
    "source": "Manually generated",
    "topic": "Science",
    "safety_flags": []
}

2. Assistant's name

Sometimes the assistant's name is included. The assistant's name is بودماغ. If you find this word, you can replace it with any other name. Here's an example:

[
    {
        "role": "user",
        "content": "أهلا شنو سميتك؟"
    },
    {
        "role": "assistant",
        "content": "انا سميتي بودماغ، ساوبني عماد الصاديق باش نساعدك فاي حاجة اللي نقد نعاون فيها."
    },
    {
        "role": "user",
        "content": "هههه سمية واعرة عجباتني"
    },
    {
        "role": "assistant",
        "content": "هههه واييه راه عندي دماغ كبير غا باش نقد نعاونك فاي حاجة الى كنت نعرف ليها."
    },
    {
        "role": "user",
        "content": "شناهيا العاصمة دالمغرب؟"
    },
    {
        "role": "assistant",
        "content": "العاصمة دالمغرب هي الرباط."
    }
]

3. Special tokens

This dataset doesn't use any special tokens. Since everyone uses different tokens, feel free to add them as needed.

Contributing

As I mentioned, I'm manually creating this dataset to ensure high quality. If you'd like to help, follow these steps:

Fork the repository.
Create a new branch.
Add your new conversations to the input_dataset.json file. Each conversation should be a list of message objects (see example below).
Run the enrich_dataset.py script in the scripts directory to enrich your conversations with metadata and append them to the global dataset.
Create a pull request.

Example: Adding to `input_dataset.json`

The input_dataset.json file should contain a list of conversations. Each conversation is itself a list of message objects, where each message has a role (either user or assistant) and a content field. For example:

[
    [
        {"role": "user", "content": "أهلا شنو سميتك؟"},
        {"role": "assistant", "content": "انا سميتي بودماغ، ساوبني عماد الصاديق باش نساعدك فاي حاجة اللي نقد نعاون فيها."}
    ],
    [
        {"role": "user", "content": "شنو تحب تشرب؟"},
        {"role": "assistant", "content": "نحب نشرب قهوة، ونتمنى انك زادة تحبها."}
    ]
]

After adding your conversations, run:

python scripts/enrich_dataset.py

This will process your new conversations and add them (with metadata) to the main dataset.

Wanna talk?

You can contact me through:

Discord: Username: imad_saddik
LinkedIn: Connect with me.
Email: [email protected].