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Hezartech Test Results and Overview


Test Results Overview

This document provides a detailed review of the test results from the latest model evaluation. The results are presented through tables and visualized with graphs to aid in the interpretation of the model's performance.

some_output


📊 Performance Metrics

The table below summarizes the key performance metrics across different datasets:

metrics_acc_f1


epoch_based_metrics


📉 Graphical Analysis

Confusion Matrix

Confusion Matrix

The confusion matrix for the Sentiment Analysis dataset. It illustrates the distribution of true positives, true negatives, false positives, and false negatives.

Metrics per Epochs

Metrics per Epochs

The metric values per epochs graph to analyze best epoch value


Connecting firms with sentiments algorithm

diagram1

OLD algorithm

diagram1

📝 Conclusion

The model demonstrates strong performance across all datasets, with particularly high accuracy and F1-scores in the Sentiment Analysis dataset. The visualizations indicate consistent improvement over time, suggesting effective tuning and optimization.

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