# Technical Document Extraction: Reweighting Module Analysis
## Image Description
The image contains two side-by-side bar charts comparing the performance of different reweighting module configurations across two evaluation metrics: **BLEU** (left) and **Rouge-L** (right). Each chart uses vertical bars to represent values, with dashed lines connecting data points to illustrate trends.
---
### **Key Labels and Axis Titles**
1. **X-Axis (Horizontal):**
- Title: *"Choice of the reweighting module"*
- Categories (left to right):
- No plugin
- 1-layer
- 2-layer
- 4-layer
- 8-layer
- 12-layer
- GPT2 Small
2. **Y-Axis (Vertical):**
- Title: *"Value"*
- Scale:
- BLEU: 0.00 to 0.30 (increments of 0.05)
- Rouge-L: 0.00 to 0.40 (increments of 0.10)
3. **Chart Titles:**
- Left Chart: *"BLEU"*
- Right Chart: *"Rouge-L"*
---
### **Data Categories and Sub-Categories**
- **Reweighting Module Configurations:**
- No plugin
- 1-layer
- 2-layer
- 4-layer
- 8-layer
- 12-layer
- GPT2 Small
- **Evaluation Metrics:**
- BLEU (left chart)
- Rouge-L (right chart)
---
### **Data Points and Trends**
#### **BLEU Chart (Left)**
- **Trend:**
- Dashed line starts at **No plugin** (~0.02), rises sharply to **1-layer** (~0.19), plateaus through **12-layer** (~0.16), then spikes at **GPT2 Small** (~0.29).
- **Values (approximate):**
| Module | Value |
|-----------------|-------|
| No plugin | 0.02 |
| 1-layer | 0.19 |
| 2-layer | 0.16 |
| 4-layer | 0.16 |
| 8-layer | 0.16 |
| 12-layer | 0.16 |
| GPT2 Small | 0.29 |
#### **Rouge-L Chart (Right)**
- **Trend:**
- Dashed line starts at **No plugin** (~0.22), rises to **1-layer** (~0.39), plateaus through **12-layer** (~0.37), then increases at **GPT2 Small** (~0.48).
- **Values (approximate):**
| Module | Value |
|-----------------|-------|
| No plugin | 0.22 |
| 1-layer | 0.39 |
| 2-layer | 0.38 |
| 4-layer | 0.38 |
| 8-layer | 0.37 |
| 12-layer | 0.37 |
| GPT2 Small | 0.48 |
---
### **Visual Components**
1. **Bars:**
- Shades of purple (light to dark) represent module complexity.
- Darker bars correspond to higher-layer configurations (e.g., GPT2 Small).
2. **Dashed Lines:**
- Black lines connect bars sequentially to highlight trends.
- No explicit legend is present, but line placement aligns with x-axis categories.
3. **Spatial Grounding:**
- **Legend:** Not explicitly visible.
- **X-Axis Placement:** Categories evenly spaced from left to right.
- **Y-Axis Placement:** Values aligned vertically with incremental markers.
---
### **Critical Observations**
1. **Performance Trends:**
- **BLEU:** GPT2 Small achieves the highest value (~0.29), outperforming all other configurations.
- **Rouge-L:** GPT2 Small also leads (~0.48), with a notable gap compared to 1-layer (~0.39).
2. **Plateaus:**
- Both metrics plateau between **2-layer** and **12-layer**, suggesting diminishing returns for intermediate configurations.
3. **No Plugin Baseline:**
- Minimal performance in both metrics (~0.02 for BLEU, ~0.22 for Rouge-L).
---
### **Conclusion**
The charts demonstrate that **GPT2 Small** consistently outperforms other reweighting module configurations across both BLEU and Rouge-L metrics. Intermediate configurations (2-layer to 12-layer) show similar performance, while the "No plugin" baseline remains significantly lower.
