\n ## Pie Charts: Self-Judgement and Self-Difficulty Evaluation for Qwen2.5-14B-Instruct ### Overview The image contains two pie charts. The left chart displays the results of a "Self-Judgement" evaluation for the Qwen2.5-14B-Instruct model. The right chart shows the "Self-Difficulty Evaluation" for the same model. Both charts represent the distribution of responses across different categories. ### Components/Axes Both charts lack explicit axes, as they are pie charts. They are labeled with titles indicating the type of evaluation. Each slice of the pie charts is labeled with a category and its corresponding percentage. **Left Chart (Self-Judgement):** * Categories: "perfect", "bad" * Percentages: 35.3%, 64.1% **Right Chart (Self-Difficulty Evaluation):** * Categories: 0, 1, 2, 3, 4, 5, 6, 7, 8 * Percentages: 6.9%, 5.2%, 5.1%, 5.4%, 5.8%, 5.6%, 8.2%, 12.0%, 44.8% ### Detailed Analysis or Content Details **Left Chart (Self-Judgement):** The pie chart is dominated by the "bad" category, representing approximately 64.1% of the responses. The "perfect" category accounts for the remaining 35.3%. **Right Chart (Self-Difficulty Evaluation):** The largest segment of this pie chart is the "8" category, representing 44.8% of the responses. The remaining categories are distributed as follows: * 0: 6.9% * 1: 5.2% * 2: 5.1% * 3: 5.4% * 4: 5.8% * 5: 5.6% * 6: 8.2% * 7: 12.0% ### Key Observations * The model frequently self-judges its responses as "bad" (64.1%). * The most common self-assessed difficulty level is 8 (44.8%). * The distribution of difficulty levels is relatively even across the lower levels (0-7), with a slight increase in responses for difficulty level 7 (12.0%). ### Interpretation The data suggests that the Qwen2.5-14B-Instruct model tends to be critical of its own responses, frequently rating them as "bad". This could indicate a conservative self-assessment strategy or a genuine awareness of limitations in its performance. The concentration of responses at difficulty level 8 suggests that the model often perceives tasks as moderately challenging. The relatively even distribution of lower difficulty levels indicates that the model encounters a range of task complexities. The fact that the model rates itself as "bad" more often than "perfect" could be a sign of a well-calibrated model that doesn't overestimate its capabilities. Further investigation would be needed to understand the specific types of responses that are categorized as "bad" and the characteristics of tasks assigned a difficulty level of 8.