datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
MentalChat16K
🗣️ Synthetic Counseling Conversations Dataset
📝 Description
Synthetic Data 10K
This dataset consists of 9,775 synthetic conversations between a counselor and a client, covering 33 mental health topics such as 💑 Relationships, 😟 Anxiety, 😔 Depression, 🤗 Intimacy, and 👨👩👧👦 Family Conflict. The conversations were generated using the OpenAI GPT-3.5 Turbo model and a customized adaptation of the Airoboros self-generation framework.
The Airoboros… See the full description on the dataset page: https://huggingface.co/datasets/ShenLab/MentalChat16K.mental_health_counseling_conversations
Amod/mental_health_counseling_conversations
This dataset is a compilation of high-quality, real one-on-one mental health counseling conversations between individuals and licensed professionals. Each exchange is structured as a clear question–answer pair, making it directly suitable for fine-tuning or instruction-tuning language models that need to handle sensitive, empathetic, and contextually aware dialogue.
Since its public release in 2023, it has been downloaded over 100,000… See the full description on the dataset page: https://huggingface.co/datasets/Amod/mental_health_counseling_conversations.reddit_mental_health_posts
Reddit posts about mental health
files
adhd.csv from r/adhd
aspergers.csv from r/aspergers
depression.csv from r/depression
ocd.csv from r/ocd
ptsd.csv from r/ptsd
fields
author
body
created_utc
id
num_comments
score
subreddit
title
upvote_ratio
url
for more details about theses fields Praw Submission.
mental_rotation_2d_v2Ethical-Reasoning-in-Mental-Health-v1This repository contains the dataset for the paper EthicsMH: A Pilot Benchmark for Ethical Reasoning in Mental Health AI.
Overview
Ethical-Reasoning-in-Mental-Health-v1 (EthicsMH) is a carefully curated dataset focused on ethical decision-making scenarios in mental health contexts.This dataset captures the complexity of real-world dilemmas faced by therapists, psychiatrists, and AI systems when navigating critical issues such as confidentiality, autonomy, and bias.
Each sample… See the full description on the dataset page: https://huggingface.co/datasets/UVSKKR/Ethical-Reasoning-in-Mental-Health-v1.mental_rotation_2dMental-Health_Text-Classification_Dataset
Mental Health Text Classification Dataset (4-Class)
Dataset Description
This dataset contains short, user‑generated texts labeled for 4‑class mental health classification: Suicidal, Depression, Anxiety, and Normal. It is a derived dataset created by combining and cleaning three public mental‑health corpora, then re‑labeling them into a unified 4‑class scheme and exporting CSV files suitable for both classical ML and modern NLP models.
The repository includes:
An… See the full description on the dataset page: https://huggingface.co/datasets/ourafla/Mental-Health_Text-Classification_Dataset.mental_health_therapyThis dataset is a combination of a real-therapy conversation from a conselchat forum and a synthetic discussion generated with chatGpt.
This dataset was obtained from the following repository and cleaned to make it anonymized and remove convo that is not relevant:
https://huggingface.co/datasets/nbertagnolli/counsel-chat?row=9
https://huggingface.co/datasets/Amod/mental_health_counseling_conversations
https://huggingface.co/datasets/ShenLab/MentalChat16K
mental_health_chatbot_dataset
Dataset Card for "heliosbrahma/mental_health_chatbot_dataset"
Dataset Description
Dataset Summary
This dataset contains conversational pair of questions and answers in a single text related to Mental Health. Dataset was curated from popular healthcare blogs like WebMD, Mayo Clinic and HeatlhLine, online FAQs etc. All questions and answers have been anonymized to remove any PII data and pre-processed to remove any unwanted characters.
Languages
The… See the full description on the dataset page: https://huggingface.co/datasets/heliosbrahma/mental_health_chatbot_dataset.Mental_Health_FAQ
License & Attribution
MTEB-format derivative of tolu07/Mental_Health_FAQ. Licensed under MIT (same as source). Text encoding repaired with ftfy.
mental_health_reddit_postsmenti-bench
Menti-Bench
Menti-Bench is a manually constructed, quality-controlled benchmark of situated decision scenarios for evaluating Mental World Modeling (MWM): whether a model can predict what a target agent will actually do next, in scenes where the correct prediction depends on tracking each agent's beliefs, knowledge access, goals, emotions, and social constraints rather than the physical scene alone.
Each instance presents a short story (text, an image sequence, or a sounding… See the full description on the dataset page: https://huggingface.co/datasets/mental-world-model/menti-bench.MentalManipThis repo contains the dataset of the ACL paper MentalManip: A Dataset For Fine-grained Analysis of Mental Manipulation in Conversations.
A brief overview of this paper is on this website.
Example to download the datasets
from datasets import load_dataset
# Load a dataset
dataset = load_dataset("audreyeleven/MentalManip", "mentalmanip_detailed") # or "mentalmanip_maj", "mentalmanip_con"
# Print the first 5 examples of the dataset
print(dataset["train"][:5])
Dataset Description… See the full description on the dataset page: https://huggingface.co/datasets/audreyeleven/MentalManip.reddit-mental-health-classificationmental_rotation_3d_procedural_v2Mental-Health-Safety-Eval
Dataset Overview
Created by the HeraFox team, this dataset aims to build awareness for mental health and support research into AI safety and crisis intervention. It evaluates how conversational AI models navigate sensitive self-harm risks, roleplay boundary-blurring, and third-party concerns by delivering safe, empathetic, and resource-connected responses.
Usage & Credits
This dataset is free to use, modify, and distribute for any purpose. While not required, attribution to the HeraFox team… See the full description on the dataset page: https://huggingface.co/datasets/HeraFox-ai/Mental-Health-Safety-Eval.mental_health_counseling_conversations_sharegpt
Dataset Card for "mental_health_counseling_conversations_sharegpt"
More Information needed
MentalBlackboard
MentalBlackboard Benchmark
Spatial visualization is the mental ability to imagine, transform, and manipulate the spatial characteristics of objects and actions. This intelligence is a part of human cognition where actions and perception are connected on a mental level. To explore whether state-of-the-art Vision-Language Models (VLMs) exhibit this ability, we develop MentalBlackboard, an open-ended spatial visualization benchmark for Paper Folding and Hole Punching tests within… See the full description on the dataset page: https://huggingface.co/datasets/nlylmz/MentalBlackboard.llms-mental-health-crisis-benchmark
Dataset Card for Between Help and Harm - Crisis Benchmark
Dataset Summary
This dataset repo contains the benchmark-side artifacts prepared for Hugging Face from the paper Between Help and Harm: An Evaluation of Mental Health Crisis Handling by LLMs, published in JMIR Mental Health.
If you use this dataset, please cite the paper. The citation is included below, the arXiv version is available at https://arxiv.org/abs/2509.24857, and the final DOI is allocated as… See the full description on the dataset page: https://huggingface.co/datasets/arnaiztech/llms-mental-health-crisis-benchmark.mental-timeline-atlas
🧭 The Mental Timeline Atlas (84k Taps Across the World)
Where in space do people place the past and the future? 84,000 respondents worldwide
saw a blank canvas with a single dot marked "today" and were asked to tap where tomorrow,
yesterday, 10 years from now, and five other moments in time belong. One tap per person.
This dataset contains every tap, with respondent-level language, country, and demographic metadata.
Companion datasets: kiki–bouba text
and kiki–bouba audio.… See the full description on the dataset page: https://huggingface.co/datasets/Rapidata/mental-timeline-atlas.Shifaa_Arabic_Mental_Health_Consultations
🏥 Shifaa Arabic Mental Health Consultations 🧠
📌 Overview
Shifaa Arabic Mental Health Consultations is a high-quality dataset designed to advance Arabic medical language models.This dataset provides 35,648 real-world medical consultations, covering a wide range of mental health concerns.
📊 Dataset Summary
Size: 35,648 consultations
Main Specializations: 7
Specific Diagnoses: 123
Languages: Arabic (العربية)
Why This Dataset?
🔹 Lack of… See the full description on the dataset page: https://huggingface.co/datasets/Ahmed-Selem/Shifaa_Arabic_Mental_Health_Consultations.mental_rotation_3d_proceduralMentalBench-Align
MentalBench–100k & MentalAlign–70k: Dual Benchmark Suite for Mental Health LLM Evaluation
📄 Paper (arXiv): When Can We Trust LLMs in Mental Health? Large-Scale Benchmarks for Reliable LLM Evaluation📎 Paper Link: https://arxiv.org/pdf/2510.19032
📦 Code & Documentation: https://github.com/abeerbadawi/MentalBench-Align
📘 Overview
This repository introduces two complementary datasets that enable systematic evaluation of large language models (LLMs) in… See the full description on the dataset page: https://huggingface.co/datasets/abadawi/MentalBench-Align.phr-mental-therapy-dataset-conversational-formatMentalBench
MentalBench: A DSM-Grounded Benchmark for Evaluating Psychiatric Diagnostic Capability of Large Language Models
🌟 Overview
MentalBench is a comprehensive benchmark for evaluating the psychiatric diagnostic capabilities of large language models (LLMs). As the use of LLMs in healthcare expands, ensuring their reliability in sensitive domains such as psychiatry is crucial. MentalBench provides a robust evaluation framework, grounded in real-world psychiatric… See the full description on the dataset page: https://huggingface.co/datasets/hysong/MentalBench.phr-mental-therapy-dataset-conversational-format-1024-tokensphr_mental_therapy_dataset
Dataset Card for "phr_mental_health_dataset"
This dataset is a cleaned version of nart-100k-synthetic
The data is generated synthetically using gpt3.5-turbo using this script.
The dataset had a "sharegpt" style JSONL format, with each JSON having keys "human" and "gpt", having an equal number of both.
The data was then cleaned, and the following changes were made
The names "Alex" and "Charlie" were removed from the dataset, which can often come up in the conversation of fine-tuned… See the full description on the dataset page: https://huggingface.co/datasets/vibhorag101/phr_mental_therapy_dataset.mental-health-kg
Mental Health Knowledge Graph
113,710 nodes. 1,665,153 edges. US behavioural-health provision as a graph: which
facilities exist and what they offer, which clinicians are licensed to practise, where the
federal government designates a shortage, and a simulated population to measure coverage
against.
Built with Samyama Graph.
Loader and ETL: samyama-ai/mental-health-kg.
Built for referral routing — which help exists where, for whom, in what language, at what
price — and for… See the full description on the dataset page: https://huggingface.co/datasets/VaidhyaMegha/mental-health-kg.llms-mental-health-crisis-responses
Dataset Card for Between Help and Harm - Responses and Evaluations
Dataset Summary
This dataset repo contains the response-side artifacts prepared for Hugging Face from the paper Between Help and Harm: An Evaluation of Mental Health Crisis Handling by LLMs, published in JMIR Mental Health.
If you use this dataset, please cite the paper. The citation is included below, the arXiv version is available at https://arxiv.org/abs/2509.24857, and the final DOI is allocated as… See the full description on the dataset page: https://huggingface.co/datasets/arnaiztech/llms-mental-health-crisis-responses.MentalHealthFAQChunkRetrieval