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README.md

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 # Dataset Card for "AGabs_finetuning"
 
-[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+Dataset is imported from CodeXGLUE and pre-processed using their script.
+Where to find in Semeru:
+The dataset can be found at /nfs/semeru/semeru_datasets/code_xglue/code-to-code/Defect-detection in Semeru
+
+CodeXGLUE -- Defect Detection
+Task Definition
+Given a source code, the task is to identify whether it is an insecure code that may attack software systems, such as resource leaks, use-after-free vulnerabilities and DoS attack. We treat the task as binary classification (0/1), where 1 stands for insecure code and 0 for secure code.
+
+Dataset
+The dataset we use comes from the paper Devign: Effective Vulnerability Identification by Learning Comprehensive Program Semantics via Graph Neural Networks. We combine all projects and split 80%/10%/10% for training/dev/test.
+
+Data Format
+Three pre-processed .jsonl files, i.e. train.jsonl, valid.jsonl, test.jsonl are present
+
+For each file, each line in the uncompressed file represents one function. One row is illustrated below.
+
+func: the source code
+target: 0 or 1 (vulnerability or not)
+idx: the index of example
+Data Statistics
+Data statistics of the dataset are shown in the below table:
+
+#Examples
+Train	126,477
+Dev	15,809
+Test	15,810