Update README.md

README.md

@@ -1,36 +1,40 @@
 ---
 configs:
-  - config_name: task1
-    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
-    data_files:
-      - split: train
-        path: data/train-task2.csv
-      - split: valid
-        path: data/valid-task2.csv
-      - split: test
-        path: data/test-task2.csv
+- config_name: task1
+  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
+  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
+- bn
 tags:
-  - Hateful-Memes
+- Hateful-Memes
+- Multimodal
+- Bengali
 size_categories:
-  - 1K<n<10K
+- 1K<n<10K
 task_categories:
-  - other
+- other
+- image-classification
+- image-to-text
 dataset_info:
-  - images_path: Memes/
-    columns:
-      - image_name: string
-      - Captions: string
-      - Labels: int32
+- images_path: Memes/
+  columns:
+  - image_name: string
+  - Captions: string
+  - Labels: int32
 ---
 
 ## Dataset Description
@@ -46,7 +50,7 @@ tailored for two tasks: (i) detecting hateful memes and (ii) detecting the socia
 
 ### Data Downloading
 
-For each task, the data examples were divided into three subsets: *train*, *valid*, and *test*.
+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)):
 
@@ -59,13 +63,13 @@ task2 = load_dataset("Eftekhar/BHM-Bengali-Hateful-Memes", "task2")  # Multiclas
 
 ### Data Format
 
-The dataset is provided in csv format and contains the following attributes:
+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": [list] Class labels.   
+    "Labels": [string] Class labels.   
 }
 ```