Update README.md

README.md

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----
-license: mit
----
+---
+license: mit
+language:
+- en
+pipeline_tag: time-series-forecasting
+tags:
+- cryptocurrency
+- sei
+- sei-network
+- price-prediction
+- time-series
+- finance
+- machine-learning
+datasets:
+- yahoo-finance
+metrics:
+- mae
+- rmse
+---
+
+# SEI Network (SEI) Price Predictor
+
+## Model Description
+This model is a **time-series forecasting model** created to predict the future price of **SEI Network (SEI)** using historical market data.  
+It identifies patterns from past price movements to estimate possible future trends.
+
+This project is intended for **educational and experimental purposes only**.
+
+## Intended Use
+- Cryptocurrency price trend analysis  
+- Time-series forecasting experiments  
+- Machine learning research on crypto assets  
+- Educational demonstrations  
+
+### Not Intended For
+- Real-time or automated trading  
+- Financial or investment advice  
+- Guaranteed price predictions  
+
+## Training Data
+The model is trained on **historical SEI price data** obtained from publicly available cryptocurrency market sources (such as Yahoo Finance or similar providers).
+
+**Input features may include:**
+- Open price  
+- High price  
+- Low price  
+- Close price  
+- Trading volume  
+
+## Model Architecture
+- Model Type: Time-series forecasting / regression  
+- Possible models: LSTM, GRU, or classical ML regression  
+- Framework: Python (TensorFlow / PyTorch / Scikit-learn)
+
+## Evaluation Metrics
+Model performance is measured using:
+- **MAE (Mean Absolute Error)**
+- **RMSE (Root Mean Squared Error)**
+
+These metrics quantify how close the predictions are to actual prices.
+
+## Limitations
+- SEI is a relatively volatile cryptocurrency  
+- Market news and on-chain events are not included  
+- Sudden price movements may reduce accuracy  
+- Historical data does not guarantee future results  
+
+## Ethical Considerations
+This model does not use personal data.  
+Users should be aware of the risks associated with cryptocurrency markets.
+
+## How to Use
+1. Provide historical SEI price data  
+2. Preprocess and normalize the data  
+3. Run the model to generate future price predictions  
+
+## Disclaimer
+This model is provided **as-is** for educational purposes only.  
+The author is **not responsible for any financial loss** arising from its use.
+
+---
+
+**Author:** jomarie04  
+**Project Type:** Educational / Experimental