Update README.md

README.md

@@ -1,3 +1,96 @@
 ---
+annotations_creators:
+- expert-generated
+- found
+configs:
+- config_name: default
+  data_files:
+  - split: validation
+    path: validation.json
+  - split: test
+    path: test.json
+dataset_info:
+  features:
+  - name: question_id
+    dtype: string
+  - name: question
+    dtype: string
+  - name: tables
+    dtype: list
+  - name: topic
+    dtype: string
+  - name: python_solution
+    dtype: string
+  - name: ground_truth
+    sequence: float
 license: mit
 ---
+## Dataset Description
+
+**KnowledgeMath** is a knowledge-intensive dataset focused on mathematical reasoning within the domain of finance. It requires the model to comprehend specialized financial terminology and to interpret tabular data presented in the questions. 
+**KnowledgeMath** includes **1200 QA examples** across 7 key areas in finance. These examples were collected from financial experts and feature detailed solution annotations in Python format.
+
+## Dataset Information
+
+- Paper: https://arxiv.org/abs/2311.09797
+- Code: https://github.com/yale-nlp/KnowledgeMath
+- Leaderboard: will be released soon!
+
+### Data Downloading and Usage
+
+All the data examples were divided into two subsets: *validation* and *test*.
+
+- **validation**: 200 examples used for model development, validation, or for those with limited computing resources.
+- **test**: 1000 examples for standard evaluation. We will not publicly release the annotated solution and answer for the test set.
+
+You can download this dataset by the following command:
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("yale-nlp/KnowledgeMath")
+```
+
+Here are some examples of how to access the downloaded dataset:
+
+```python
+# print the first example on the validation set
+print(dataset["validation"][0])
+
+# print the first example on the test set
+print(dataset["test"][0])
+```
+
+### Data Format
+
+The dataset is provided in json format and contains the following attributes:
+
+```json
+{
+    "question_id": [string] The question id,
+    "question": [string] The question text,
+    "tables": [list] List of Markdown-format tables associated with the question, 
+    "python_solution": [string] Python-format and executable solution by financial experts. The code is written in a clear and executable format, with well-named variables and a detailed explanation,
+    "ground_truth": [integer] Executed result of `python solution`, rounded to three decimal places,
+    "topic": [string] The related financial area of the question
+}
+```
+
+### Automated Evaluation
+
+To automatically evaluate a model on **KnowledgeMath**, please refer to our GitHub repository [here](https://github.com/yale-nlp/KnowledgeMath).
+
+## Citation
+
+If you use the **KnowledgeMath** dataset in your work, please kindly cite the paper:
+
+```
+@misc{zhao2023knowledgemath,
+      title={KnowledgeMath: Knowledge-Intensive Math Word Problem Solving in Finance Domains}, 
+      author={Yilun Zhao and Hongjun Liu and Yitao Long and Rui Zhang and Chen Zhao and Arman Cohan},
+      year={2023},
+      eprint={2311.09797},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+```