Update README.md

README.md

@@ -10,24 +10,31 @@ tags:
 - bert
 ---
 
-Model Description
+# **Model Description**
 
-This model predicts the star rating (1-5) of a Yelp review based on its text content. It was trained using GPT-2 and BERT, with BERT achieving the best performance at 75% validation accuracy. The model addresses class imbalance using weighted loss and optimizes hyperparameters to enhance generalization.
+This model predicts the star rating (1 - 5) of a Yelp review based on its text content. It was trained using **GPT-2** and **BERT**, with **BERT** achieving the best performance at **75%** validation accuracy. The model addresses class imbalance using weighted loss and optimizes hyperparameters to enhance generalization.
 
-Training Details
+# **Training Details**
 
-Dataset: Yelp Reviews dataset (100,000 samples used)
+- **Dataset**: Yelp Reviews dataset (100,000 samples used)
 
-Preprocessing:
+- **Preprocessing**:
 
-GPT-2 Tokenizer with Byte-Pair Encoding (BPE) for rare words
+  - **GPT-2 Tokenizer** with **Byte-Pair Encoding (BPE)** for rare words
+  - Truncation (128 tokens) and padding for uniform input size
 
-Truncation (128 tokens) and padding for uniform input size
+- **Models Trained**:
 
-Models Trained:
+  - **GPT-2**: Fine-tuned with a custom classification head, achieving **67% validation accuracy**
 
-GPT-2: Fine-tuned with a custom classification head, achieving 67% validation accuracy
+  - **BERT**: Fine-tuned with bidirectional attention, achieving **75% validation accuracy**
 
-BERT: Fine-tuned with bidirectional attention, achieving 75% validation accuracy
+- **Loss Function**: Weighted **Cross-Entropy Loss** to counteract class imbalance
 
-Loss Function: Weighted Cross-Entropy Loss to counteract class imbalance
+# **Limitations**
+
+- Performance may degrade on **highly informal or extremely short reviews**
+
+- **Class imbalance** still affects predictions for underrepresented ratings
+
+- Model was trained on **English-language** reviews only