F1 Score
79.5%
Needs improvement
+4.8% from v2.0Precision
82.5%
Good
+3.9% from v2.0Recall
76.8%
Needs improvement
+5.6% from v2.0Accuracy
84.2%
Good
+2.8% from v2.0Executive Summary
Overall performance assessment of the Unicorn Classification Agent
Iteration Comparison (v2.5 vs v2.0)
F1 Score
+4.8%
Precision
+3.9%
Recall
+5.6%
Overall F1 Score: 79.5%
The model shows moderate performance. There's room for improvement in balancing precision and recall.
Precision: 82.5%
The model favors precision over recall, meaning it's more conservative in its unicorn classifications but may miss some valid cases.
Recall: 76.8%
The model has lower recall compared to precision, indicating it may miss some unicorn-related content but is more accurate when it does make a positive classification.
Key Improvements from Previous Iteration
- Enhanced context awareness and added more diverse training examples, improving overall F1 score by 5%.
Key Insights
- Financial Context performance: 78.1% F1 Score
- Mythological References performance: 80.3% F1 Score
- Most common error type: Mythological References
- Top recommendation: Enhance training on financial metaphors