README.md

metadata

language:
  - en
license: apache-2.0
size_categories:
  - 10K<n<100K
task_categories:
  - text-generation
dataset_info:
  features:
    - name: conv_id
      dtype: string
    - name: situation
      dtype: string
    - name: emotion
      dtype: string
    - name: conversations
      list:
        - name: content
          dtype: string
        - name: role
          dtype: string
  splits:
    - name: train
      num_bytes: 10022798
      num_examples: 17844
    - name: validation
      num_bytes: 1585269
      num_examples: 2763
    - name: test
      num_bytes: 1497551
      num_examples: 2542
  download_size: 7057115
  dataset_size: 13105618
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: validation
        path: data/validation-*
      - split: test
        path: data/test-*
tags:
  - empathetic
  - ED
  - dialogue

Empathetic Dialogues for LLM

 This repository contains a reformatted version of the Empathetic Dialogues dataset, tailored for seamless integration with Language Model (LLM) training and inference. The original dataset's format posed challenges for direct application in LLM tasks, prompting us to restructure and clean the data. 

Data Restructuring

 We have implemented the following changes to enhance the dataset's usability: 

1. Merged dialogues with the same conv_id, treating each conv_id as an independent dialogue session.
2. Assigned the user role to the initiator of each dialogue session, followed by assistant for the subsequent message, and so on, alternating between the two roles.
3. Retained the original conv_id, emotion, and situation fields to facilitate the construction of instructions.
4. Removed the utterance_id, selfeval, and tags fields to streamline the data.
5. Replaced instances of '_comma_' with ',' for improved readability.



Data Format

 Each entry in the reformatted dataset consists of the following fields: 

• conversations: A list of dictionaries, where each dictionary represents a turn in the dialogue and contains:
  • role: A string indicating the speaker's role, either user or assistant.
  • content: A string containing the dialogue content.
• conv_id: A string representing the unique identifier for the dialogue session.
• emotion: A string indicating the emotional label associated with the dialogue (corresponds to the context field in the original dataset).
• situation: A string describing the situational label for the dialogue (corresponds to the prompt field in the original dataset).



Important Note

 In the original Empathetic Dialogues dataset, not all dialogue sessions have an even number of conversation turns. To maintain the integrity of the dataset, we have preserved this characteristic in our reformatted version. However, this peculiarity may lead to potential bugs when directly applying the dataset to LLM training or inference. Users should be mindful of this aspect when working with the data. 

Dataset Statistics

Dataset	Total Turn	Average Turn	Average Length
Train	76,673	4.296	39.564
Validation	12,030	4.354	39.045
Test	10,943	4.305	39.490