Update README.md

README.md

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----
-license: mit
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+---
+license: mit
+---
+
+# MathGPT-2 (distilgpt2 Fine-Tuned for Arithmetic)
+
+This model is a **fine-tuned version of DistilGPT-2** on a custom dataset consisting exclusively of arithmetic problems and their answers. The goal of this model is to act as a **calculator** that can solve basic arithmetic problems.
+
+## Model Description
+
+The model was trained using a dataset of simple arithmetic expressions, including addition, subtraction, multiplication, and division. The training data was generated using Python and ensured to have **no duplicate expressions**.
+
+### Key Features:
+- **Solves basic arithmetic** (addition, subtraction, multiplication, division)
+- Can **handle simple problems** like `12 + 5 =`
+- Fine-tuned version of `distilgpt2` on a math-specific dataset
+- Trained for **10 epochs** (further improvements can be made by training for more epochs)
+
+## Model Details
+
+- **Model architecture**: DistilGPT-2
+- **Training duration**: 10 epochs (could be improved further)
+- **Dataset**: Generated math expressions like `12 + 5 = 17`
+- **Tokenization**: Standard GPT-2 tokenizer
+- **Fine-tuned on**: Simple arithmetic operations
+
+## Intended Use
+
+This model is designed to:
+- **Answer basic arithmetic problems** (addition, subtraction, multiplication, division).
+- It can generate answers for simple problems like `12 * 6 = ?`.
+
+### Example:
+
+**Input**:
+```
+13 + 47 =
+```
+
+**Output**:
+```
+60
+```
+
+
+## Training Data
+
+The training dataset was generated using Python, consisting of random arithmetic expressions (addition, subtraction, multiplication, division) between numbers from 1 to 100. The expressions were formatted as:
+
+```
+2 + 3 = 5
+100 - 25 = 75
+45 * 5 = 225
+100 / 25 = 4
+```
+
+No duplicate expressions were used, ensuring the model learns unique patterns.
+
+## Fine-Tuning
+
+This model was fine-tuned from the `distilgpt2` base model for 10 epochs. 
+
+---
+
+## Limitations
+
+- **Basic Arithmetic Only**: The model can only handle basic arithmetic problems like addition, subtraction, multiplication, and division. It does not handle more complex operations like exponentiation, logarithms, or advanced algebra.
+- **Limited Training Duration**: While trained for 10 epochs, more epochs or data diversity may improve the model's performance further.
+- **No real-time validation**: The model's performance varies, and there are still inaccuracies in answers for some problems.