---
dataset_info:
  features:
  - name: conversations
    list:
    - name: content
      dtype: string
    - name: role
      dtype: string
    - name: strategy
      dtype: string
  - name: emotion
    dtype: string
  - name: experience
    dtype: string
  - name: problem
    dtype: string
  - name: situation
    dtype: string
  splits:
  - name: train
    num_bytes: 3087133
    num_examples: 910
  - name: validation
    num_bytes: 662566
    num_examples: 195
  - name: test
    num_bytes: 669299
    num_examples: 195
  download_size: 2158864
  dataset_size: 4418998
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: validation
    path: data/validation-*
  - split: test
    path: data/test-*
license: apache-2.0
task_categories:
- text-generation
- text-classification
language:
- en
tags:
- esconv
- empathetic
size_categories:
- 1K<n<10K
---
# ESCONV for LLM
 This repository contains a reformatted version of the ESCONV 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
1. Assigned the `user` role to the `usr`, `assistant` role to the `sys`.
2. Removed the `survey_scor` and 'supporter' fields to streamline the data.

## 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.
  - strategy: A string containing the strategy of current dialogue content, if role is user, strategy is NONE.
- emotion: A string indicating the emotional label associated with the dialogue (corresponds to the emotion_type field in the original dataset).
- situation: A string describing the situational label for the dialogue (corresponds to the situation field in the original dataset).
- problem: A string describing the problem label for the user (corresponds to the problem_type field in the original dataset).
- experience: A string, corresponds to the experience_type field in the original dataset.


## Dataset Statistics

| Dataset     | Total Turn | Average Turn | Average Length |
|-------------|------------|--------------|----------------|
| Train       | 26,648     | 29.284       | 14.547         |
| Validation  | 5,678      | 29.118       | 14.630         |
| Test        | 6,039      | 30.969       | 13.756         |