README.md

---
configs:
- config_name: task1
  dataset_name: "CUET-NLP/BHM-Bengali-Hateful-Memes"  # Add this line to explicitly set namespace
  data_files:
  - split: train
    path: data/train-task1.csv
  - split: valid
    path: data/valid-task1.csv
  - split: test
    path: data/test-task1.csv
- config_name: task2
  dataset_name: "CUET-NLP/BHM-Bengali-Hateful-Memes"
  data_files:
  - split: train
    path: data/train-task2.csv
  - split: valid
    path: data/valid-task2.csv
  - split: test
    path: data/test-task2.csv
license: mit
language:
- bn
tags:
- Hateful-Memes
- Multimodal
- Bengali
size_categories:
- 1K<n<10K
task_categories:
- other
- image-classification
- image-to-text
dataset_info:
- images_path: Memes/
  columns:
  - image_name: string
  - Captions: string
  - Labels: int32
---

## Dataset Description

**BHM** is a novel multimodal dataset for Bengali Hateful Memes detection. The dataset consists of **7,148** memes with Bengali as well as code-mixed captions, 
tailored for two tasks: (i) detecting hateful memes and (ii) detecting the social entities they target (i.e., Individual, Organization, Community, and Society).

## Paper Information

- Paper: https://aclanthology.org/2024.acl-long.454/
- Code: https://github.com/eftekhar-hossain/Bengali-Hateful-Memes/tree/main


### Data Downloading

The data examples were divided into three subsets for each task: *train*, *valid*, and *test*.

You can download this dataset by the following command (make sure that you have installed [Huggingface Datasets](https://huggingface.co/docs/datasets/quickstart)):

```python
from datasets import load_dataset

task1 = load_dataset("Eftekhar/BHM-Bengali-Hateful-Memes", "task1")  # Binary Classification
task2 = load_dataset("Eftekhar/BHM-Bengali-Hateful-Memes", "task2")  # Multiclass Classification
```

### Data Format

The dataset is provided in CSV format and contains the following attributes:

```csv
{
    "image_name": [string] The name of the image,
    "Captions": [string] Embedded text on the corresponding images
    "Labels": [string] Class labels.   
}
```


## Citation

If you use the **BHM** dataset in your work, please kindly cite the paper using this BibTeX:

```
@article{hossain2024deciphering,
  title={Deciphering Hate: Identifying Hateful Memes and Their Targets},
  author={Hossain, Eftekhar and Sharif, Omar and Hoque, Mohammed Moshiul and Preum, Sarah M},
  journal={arXiv preprint arXiv:2403.10829},
  year={2024}
}
```