Update README.md

README.md

@@ -1,8 +1,6 @@
 ---
 title: Image App Space
 emoji: 🔥
-colorFrom: red
-colorTo: yellow
 sdk: gradio
 sdk_version: 5.47.0
 app_file: app.py
@@ -11,4 +9,29 @@ license: mit
 short_description: A simple  user-facing interface for an image model
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# AutoGluon Sign Identification Predictor
+
+This repository contains a trained MultiModalPredictor from the AutoGluon library, which was trained to identify signs from images. Which can also be found in the files and versions section under AutoML_for_Neural_Networks
+
+# Dataset
+The model was trained on the ecopus/sign_identification dataset. The augmented split was used for training and validation, while the original split was used for the final evaluation of the model's performance.
+
+# Model
+The model is borrowed from its-zion-18/sign-image-autogluon-predictor model.
+
+# Evaluation Results
+
+The final performance of the best model on the original dataset is as follows:
+
+- **Accuracy**: `1.0000`
+- **Weighted F1**: `1.0000`
+
+# Potential Errors
+The augmented split in the ecopus/sign_identification dataset is specifically designed to be an artificially expanded version of the original split. 
+The images in the augmented set are simple transformations—like rotations, flips, or slight color changes—of the images in the original set.
+The code then trains the model on a portion of the augmented data (df_aug_train) and evaluates it on the original data (df_orig). 
+Because the model was trained on data that is derived directly from the evaluation data, it's not actually seeing truly "new" information during the final test. 
+Which could be leading to data leakage and overfitting
+
+# Contact
+Feel free to contact me for any questions or concerns: aslann@cmu.edu