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README.md

@@ -1,53 +1,53 @@
----
-language: en
-license: mit
-tags:
-- financial-forecasting
-- stock-prediction
-- time-series
-- pytorch
-- ara-ai
-- ensemble-learning
-datasets:
-- yfinance
-metrics:
-- accuracy
-- mse
----
-
-# Ara AI (ARA.AI) - Financial Prediction Engine
-
-## Overview
-Ara AI is an advanced financial prediction system designed for multi-asset forecasting. This repository contains the latest weights for the ensemble models trained on market data.
-
-## Model Architecture
-The system employs a sophisticated ensemble architecture:
-- **Feature Extraction**: 44+ technical indicators (RSI, MACD, Bollinger Bands, ATR, etc.)
-- **Neural Core**: A large PyTorch model with 4M+ parameters
-- **Attention Mechanism**: Multi-head attention for identifying key temporal features
-- **Ensemble Heads**: Specialized prediction heads inspired by XGBoost, LightGBM, Random Forest, and Gradient Boosting
-- **Dynamic Weighting**: Softmax-based attention weights for weighted prediction averaging
-
-## Latest Training Stats (2026-01-12 06:24:31)
-- **Last Trained Symbol**: XBIO
-- **Validation Accuracy**: 98.5%
-- **Validation Loss (MSE)**: 0.00016297248657792807
-- **Total Unique Symbols in Training History**: N/A
-
-## Continuous Training
-This model is part of a self-evolving system. It is retrained daily on a rotation of 6,800+ tickers and 20+ forex pairs to maintain high accuracy across different market conditions and time horizons (1D, 1H).
-
-## Usage
-### Loading the model
-```python
-import torch
-from meridianalgo.unified_ml import UnifiedStockML
-
-# Download the model file from this repo first
-ml = UnifiedStockML(model_path="stock_AAPL.pt")
-prediction = ml.predict_ultimate("AAPL", days=5)
-print(prediction)
-```
-
-## Disclaimer
-**Not Financial Advice.** This software is for educational purposes only. Trading involves significant risk. The authors are not responsible for any financial losses incurred.
+---
+language: en
+license: mit
+tags:
+- financial-forecasting
+- stock-prediction
+- time-series
+- pytorch
+- ara-ai
+- ensemble-learning
+datasets:
+- yfinance
+metrics:
+- accuracy
+- mse
+---
+
+# Ara AI (ARA.AI) - Financial Prediction Engine
+
+## Overview
+Ara AI is an advanced financial prediction system designed for multi-asset forecasting. This repository contains the latest weights for the ensemble models trained on market data.
+
+## Model Architecture
+The system employs a sophisticated ensemble architecture:
+- **Feature Extraction**: 44+ technical indicators (RSI, MACD, Bollinger Bands, ATR, etc.)
+- **Neural Core**: A large PyTorch model with 4M+ parameters
+- **Attention Mechanism**: Multi-head attention for identifying key temporal features
+- **Ensemble Heads**: Specialized prediction heads inspired by XGBoost, LightGBM, Random Forest, and Gradient Boosting
+- **Dynamic Weighting**: Softmax-based attention weights for weighted prediction averaging
+
+## Latest Training Stats (2026-01-17 21:07:28)
+- **Last Trained Symbol**: AAPL
+- **Validation Accuracy**: N/A%
+- **Validation Loss (MSE)**: 0.00882477033883333
+- **Total Unique Symbols in Training History**: 1
+
+## Continuous Training
+This model is part of a self-evolving system. It is retrained daily on a rotation of 6,800+ tickers and 20+ forex pairs to maintain high accuracy across different market conditions and time horizons (1D, 1H).
+
+## Usage
+### Loading the model
+```python
+import torch
+from meridianalgo.unified_ml import UnifiedStockML
+
+# Download the model file from this repo first
+ml = UnifiedStockML(model_path="stock_AAPL.pt")
+prediction = ml.predict_ultimate("AAPL", days=5)
+print(prediction)
+```
+
+## Disclaimer
+**Not Financial Advice.** This software is for educational purposes only. Trading involves significant risk. The authors are not responsible for any financial losses incurred.