Update README.md

README.md

@@ -26,4 +26,57 @@ tags:
 pretty_name: relative-positioning
 size_categories:
 - 10K<n<100K
----
+---
+# Dataset Card for Dataset Name
+
+This dataset aims to teach LLMs relative positioning (e.g. above, left from, below, etc.), 
+which in my findings most LLMs, even SOTA where not able to produce under all circumstances.
+Will be pushing a fine-tuned mixtral-7x8B with this dataset.
+
+## Dataset Details
+
+### Dataset Description
+
+Contains Data for relative positioning on a grid(256, 256).
+Assumes Origin [0, 0] is in the bottom left.
+Two Objects (Object 1, Object 2) are randomly created.
+Answer is there relative position to one another.
+
+- **Curated by:** [Antoine Angert]
+- **Language(s) (NLP):** [English]
+- **License:** [apache-2.0]
+
+## Uses
+
+### Direct Use
+
+Can be used to fine-tune Language Models.
+(Althought so far not been tested, will update)
+
+## Dataset Structure
+
+Features:
+Prompt(String), Response(String)
+
+## Dataset Creation
+
+### Curation Rationale
+
+I did some testing to see how well LLMs are able to handle positional data(2D, 3D).
+I found that most small models (tested: llama-7B, llama-13B, mistral-7B) have very poor positional understanding.
+Most bigger Models (tested: gpt-3.5-turbo, gpt-4, llama-70B, mixtral-7x8B) have a fairly good positional understanding, as long as no other context is provided.
+When I tried using positional reasoning with some other unrelated context, the performance of these bigger models dropped imensly.
+This is my first attempt of trying to embed this understanding directly into the models and not throught context.
+
+#### Data Collection and Processing
+
+The dataset was generated using a python script.
+
+## Dataset Card Authors [optional]
+
+Antoine Angert
+
+## Dataset Card Contact
+
+Contact under:
+antoine.angert@hsbi.de