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---
language:
- en
license: apache-2.0
size_categories:
- 1K<n<10K
task_categories:
- text-generation
- text-classification
dataset_info:
features:
- name: experience_type
dtype: string
- name: emotion_type
dtype: string
- name: problem_type
dtype: string
- name: situation
dtype: string
- name: survey_score
struct:
- name: seeker
struct:
- name: empathy
dtype: string
- name: final_emotion_intensity
dtype: string
- name: initial_emotion_intensity
dtype: string
- name: relevance
dtype: string
- name: supporter
struct:
- name: relevance
dtype: string
- name: seeker_question1
dtype: string
- name: seeker_question2
dtype: string
- name: supporter_question1
dtype: string
- name: supporter_question2
dtype: string
- name: conversations
list:
- name: content
dtype: string
- name: role
dtype: string
- name: strategy
dtype: string
splits:
- name: train
num_bytes: 3089088
num_examples: 910
- name: test
num_bytes: 668538
num_examples: 195
- name: valid
num_bytes: 663512
num_examples: 195
download_size: 2191251
dataset_size: 4421138
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
- split: valid
path: data/valid-*
tags:
- esconv
- empathetic
---
# 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 | |