## Heatmap: GPT-2 Medium Head Analysis
### Overview
The image presents two heatmaps, each analyzing the heads of a GPT-2 medium model. The left heatmap focuses on "Name Copying" heads, while the right heatmap focuses on "Country to Capital" heads. Both heatmaps share a similar structure, displaying the interaction between layers (x-axis) and heads (y-axis). The color intensity represents a score, with yellow indicating higher scores and dark purple indicating lower scores. 'Circuits Components Reused' classifications are marked with an "X" on each heatmap.
### Components/Axes
* **Titles:**
* Left: "GPT-2 medium: Name Copying heads"
* Right: "GPT-2 medium: Country to capital heads"
* **Axes:**
* X-axis (both heatmaps): "Layer" with ticks from 0 to 22 in increments of 2.
* Y-axis (both heatmaps): "Head" with ticks from 0 to 15.
* **Color Scales:**
* Left: "Name Copying score" ranging from 0.0 to 1.0.
* Right: "Country to capital score" ranging from 0.0 to 1.0.
* **Legend (both heatmaps):** Located in the lower-left corner of each heatmap.
* Text: "'Circuits Components Reused' classifications"
* Symbol: "X"
* Left: "Mover Heads"
* Right: "Capital heads"
### Detailed Analysis
#### Left Heatmap: Name Copying Heads
* **General Trend:** The heatmap is mostly dark purple, indicating low "Name Copying" scores across most layer-head combinations. There are a few scattered areas with higher scores (green and yellow).
* **Mover Heads (marked with "X"):**
* Layer 1, Head 0: Not a mover head.
* Layer 8, Head 5: Mover Head.
* Layer 15, Head 13: Mover Head.
* Layer 14, Head 15: Mover Head.
* Layer 16, Head 15: Mover Head.
* Layer 18, Head 15: Mover Head.
* Layer 20, Head 15: Mover Head.
* Layer 22, Head 15: Mover Head.
* Layer 14, Head 14: Mover Head.
* Layer 16, Head 14: Mover Head.
* **Specific Data Points:**
* Layer 6, Head 0: Score ~0.8
* Layer 10, Head 8: Score ~0.6
* Layer 14, Head 15: Score ~0.8
* Layer 16, Head 15: Score ~0.8
* Layer 18, Head 15: Score ~0.6
* Layer 20, Head 15: Score ~0.6
* Layer 22, Head 15: Score ~0.6
#### Right Heatmap: Country to Capital Heads
* **General Trend:** Similar to the left heatmap, this one is also predominantly dark purple, indicating low "Country to Capital" scores. There are a few scattered areas with higher scores.
* **Capital Heads (marked with "X"):**
* Layer 12, Head 5: Capital Head.
* Layer 14, Head 13: Capital Head.
* Layer 18, Head 1: Capital Head.
* Layer 20, Head 13: Capital Head.
* Layer 20, Head 14: Capital Head.
* Layer 8, Head 0: Capital Head.
* **Specific Data Points:**
* Layer 12, Head 5: Score ~0.6
* Layer 14, Head 13: Score ~0.6
* Layer 18, Head 1: Score ~0.8
* Layer 20, Head 13: Score ~0.2
* Layer 20, Head 14: Score ~0.2
* Layer 8, Head 0: Score ~0.6
* Layer 22, Head 0: Score ~0.8
### Key Observations
* Both heatmaps show sparse activation patterns, with most layer-head combinations having low scores.
* The "Mover Heads" and "Capital Heads" are concentrated in specific layers and heads, suggesting specialized roles within the GPT-2 model.
* The "Name Copying" task seems to have more active heads in the later layers (14-22) compared to the "Country to Capital" task.
### Interpretation
The heatmaps provide insights into how different heads within the GPT-2 medium model contribute to specific tasks. The sparse activation patterns suggest that only a subset of heads are actively involved in "Name Copying" and "Country to Capital" tasks. The concentration of "Mover Heads" and "Capital Heads" in specific layers and heads indicates that these heads may have learned specialized functions related to these tasks. The difference in activation patterns between the two tasks suggests that different sets of heads are utilized for different types of knowledge processing. The data suggests that the model has learned to distribute the workload across its heads, with some heads specializing in specific tasks or sub-tasks.
