Update README.md

README.md

@@ -29,21 +29,12 @@ This model predicts the reading grade level of text using ModernBERT, trained on
 - **Task:** Text Readability Assessment (Regression)
 - **Framework:** PyTorch
 - **Base Model:** `answerdotai/ModernBERT-base`
-- **Training Data:** Custom readability dataset with Lexile scores and Flesch-Kincaid Grade Levels
+- **Training Data:** [CLEAR dataset](https://github.com/scrosseye/CLEAR-Corpus)
 - **Performance:**
   - RMSE: 1.4143198236928092
   - R²: 0.8125544567620288
 - **Output:** Predicted grade level (0-12)
 
-## Intended Use
-
-This model is designed to help educators, content creators, and publishers assess the reading level difficulty of texts. It can be used for:
-
-- Determining appropriate content for different age groups and reading abilities
-- Ensuring instructional materials match student proficiency levels
-- Simplifying complex text to increase accessibility
-- Creating a consistent measurement of text complexity across materials
-
 ## Usage
 
 ```python
@@ -115,17 +106,3 @@ This model was fine-tuned on a custom dataset created by augmenting texts from v
 3. Averaging grade level metrics for a more reliable target
 4. Fine-tuning ModernBERT with a regression head
 5. Optimizing for minimum RMSE and maximum R²
-
-## Citation
-
-If you use this model in your research, please cite:
-
-```
-@misc{modernbert-grade-predictor,
-  author = {Kiddom},
-  title = {Text Readability Grade Predictor},
-  year = {2023},
-  publisher = {Hugging Face},
-  howpublished = {\url{https://huggingface.co/{repo_id}}}
-}
-```