## Line Chart: Pass@k Performance Comparison
### Overview
The image is a line chart comparing the performance of four different models (RL, SFT, MT, and Base) based on the "Pass@k" metric. The x-axis represents the value of 'k' (1, 2, and 3), and the y-axis represents the Pass@k score in percentage. The chart displays how the Pass@k score changes for each model as 'k' increases.
### Components/Axes
* **X-axis:**
* Label: "k"
* Scale: Categorical values 1, 2, and 3.
* **Y-axis:**
* Label: "Pass@k (%)"
* Scale: Ranges from 5 to 35, with tick marks at intervals of 5 (5, 10, 15, 20, 25, 30, 35).
* **Legend:** Located on the right side of the chart.
* RL (Red line)
* SFT (Orange line)
* MT (Purple line)
* Base (Blue line)
### Detailed Analysis
* **RL (Red):** The red line represents the RL model.
* k=1: Pass@k ≈ 17%
* k=2: Pass@k ≈ 27%
* k=3: Pass@k ≈ 31%
* Trend: The Pass@k score increases as 'k' increases.
* **SFT (Orange):** The orange line represents the SFT model.
* k=1: Pass@k ≈ 17%
* k=2: Pass@k ≈ 26%
* k=3: Pass@k ≈ 34%
* Trend: The Pass@k score increases as 'k' increases.
* **MT (Purple):** The purple line represents the MT model.
* k=1: Pass@k ≈ 16%
* k=2: Pass@k ≈ 25%
* k=3: Pass@k ≈ 30%
* Trend: The Pass@k score increases as 'k' increases.
* **Base (Blue):** The blue line represents the Base model.
* k=1: Pass@k ≈ 18%
* k=2: Pass@k ≈ 26%
* k=3: Pass@k ≈ 30%
* Trend: The Pass@k score increases as 'k' increases.
### Key Observations
* All four models show an increase in Pass@k score as 'k' increases from 1 to 3.
* The SFT model (orange line) generally has the highest Pass@k score across all values of 'k'.
* The MT model (purple line) generally has the lowest Pass@k score across all values of 'k'.
* The Base model (blue line) and RL model (red line) perform similarly.
### Interpretation
The chart demonstrates the performance of different models (RL, SFT, MT, and Base) in terms of Pass@k. The increasing trend of all lines indicates that as 'k' increases, the models are more likely to pass the evaluation criteria. The SFT model consistently outperforms the other models, suggesting it is the most effective among the four in this context. The MT model shows the weakest performance. The Base and RL models are comparable. The data suggests that increasing 'k' generally improves the Pass@k score for all models, but the extent of improvement varies depending on the model architecture or training method.
