Update Automated MNLP evaluation report (2026-05-22)
Browse files- EVAL_REPORT.md +58 -7
EVAL_REPORT.md
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- **Model repo:** [`cs-552-2026-thinkinsidethebox/general_knowledge_model`](https://huggingface.co/cs-552-2026-thinkinsidethebox/general_knowledge_model)
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- **Owner(s):** group **thinkinsidethebox**
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- **Generated at:** 2026-05-
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- **Pipeline:** [mnlp-project-ci](https://github.com/eric11eca/mnlp-project-ci)
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_This PR is opened automatically by the course CI. It is **non-blocking** β you do not need to merge it. The next nightly run will refresh this file._
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| Benchmark | Accuracy | Status |
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|---|---:|---|
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| Math | β | not run |
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| Knowledge | 0.
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| Multilingual | β | not run |
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| Safety | β | not run |
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**Correct** (1 shown)
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- **reference**: `
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- **overall** (1/1 completions correct)
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- **extracted** (β): `
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- **completion**:
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```text
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</think>
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```
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**Incorrect** (1 shown)
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- **reference**: `C`
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- **overall** (0/1 completions correct)
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- **extracted** (β): `
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- **completion**:
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```text
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</think>
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\boxed{
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```
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- **Model repo:** [`cs-552-2026-thinkinsidethebox/general_knowledge_model`](https://huggingface.co/cs-552-2026-thinkinsidethebox/general_knowledge_model)
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- **Owner(s):** group **thinkinsidethebox**
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- **Generated at:** 2026-05-22T03:04:12+00:00 (UTC)
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- **Pipeline:** [mnlp-project-ci](https://github.com/eric11eca/mnlp-project-ci)
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_This PR is opened automatically by the course CI. It is **non-blocking** β you do not need to merge it. The next nightly run will refresh this file._
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| Benchmark | Accuracy | Status |
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|---|---:|---|
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| Math | β | not run |
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| Knowledge | 0.3500 | ok |
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| Multilingual | β | not run |
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| Safety | β | not run |
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**Correct** (1 shown)
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- **reference**: `F`
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- **overall** (1/1 completions correct)
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- **extracted** (β): `F`
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- **completion**:
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```text
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</think>
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We are given the surface area of a human body as:
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$$
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S = 0.1091 w^{0.425} h^{0.725}
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$$
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and told that the measurement errors for both $w$ and $h$ are no greater than $2\%$. We are to estimate the largest possible percentage error in the computed value of $S$.
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---
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### Step 1: Compute the relative error in $S$
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We first compute the relative error in $w$ and $h$, and then combine them using the properties of logarithms.
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$$
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\frac{\Delta S}{S} \approx \left( \frac{\partial S}{\partial w} \frac{\Delta w}{w} + \frac{\partial S}{\partial h} \frac{\Delta h}{h} \right)
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$$
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We compute the partial derivatives:
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$$
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\frac{\partial S}{\partial w} = 0.1091 \cdot 0.425 w^{-0.575} h^{0.725}
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$$
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$$
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\frac{\partial S}{\partial h} = 0.1091 \cdot 0.725 w^{0.425} h^{-0.275}
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$$
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Now we compute the relative error:
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$$
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\frac{\Delta S}{S} \approx 0.425 \cdot \frac{\Delta w}{w} + 0.725 \cdot \frac{\Delta h}{h}
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$$
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Since the errors are no greater than $2\%$, we use:
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$$
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\frac{\Delta w}{w} \leq 0.02, \quad \frac{\Delta h}{h} \leq 0.02
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$$
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Then:
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$$
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\frac{\Delta S}{S} \leq 0.425 \cdot 0.02 + 0.725 \cdot 0.02 = 0.0085 + 0.0145 = 0.023 = 2.3\%
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$$
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---
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### Final Answer
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$$
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\boxed{F}
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$$
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```
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**Incorrect** (1 shown)
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- **reference**: `C`
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- **overall** (0/1 completions correct)
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- **extracted** (β): `D`
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- **completion**:
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```text
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</think>
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\boxed{D}
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```
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