GPT

For Model Evaluation Report

Model: [Model name, version] Evaluation Date: [When] Data Split: [Train/Val/Test sizes, dates] Performance Metrics: Overall: [Accuracy, RMSE, AUC, or task-specific metrics] By Segment: [Performance breakdown by user typ

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**Model**: [Model name, version]
**Evaluation Date**: [When]
**Data Split**: [Train/Val/Test sizes, dates]

**Performance Metrics**:
- Overall: [Accuracy, RMSE, AUC, or task-specific metrics]
- By Segment: [Performance breakdown by user type/geography/etc.]
- Baseline Comparison: [vs. previous model, vs. industry benchmark]

**Analysis**:
- Strengths: [What does this model do well?]
- Weaknesses: [What does it struggle with?]
- Error Analysis: [Common failure modes, false positives, false negatives]

**Inference**:
- Latency: [p50, p99, avg]
- Throughput: [Requests/second on target hardware]
- Cost: [Per-prediction cost estimate]

**Recommendation**: [Ship, iterate, reject. Why?]
**Next Steps**: [If shipping: deployment plan. If iterating: next experiments]

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