## Chart Type: Line Graphs Comparing Model Performance ### Overview The image contains two line graphs comparing the performance of two versions of the Mistral-7B model (v0.1 and v0.3) on various question-answering tasks. The graphs plot "Answer Accuracy" against "Layer" for different question-answering datasets, distinguishing between question-anchored (Q-Anchored) and answer-anchored (A-Anchored) approaches. ### Components/Axes * **Titles:** * Left Graph: "Mistral-7B-v0.1" * Right Graph: "Mistral-7B-v0.3" * **Y-axis (Answer Accuracy):** * Label: "Answer Accuracy" * Scale: 0 to 100, with tick marks at 0, 20, 40, 60, 80, and 100. * **X-axis (Layer):** * Label: "Layer" * Scale: 0 to 30, with tick marks at intervals of 10. * **Legend (bottom of the image):** * Q-Anchored (PopQA): Solid Blue Line * A-Anchored (PopQA): Dashed Brown Line * Q-Anchored (TriviaQA): Dotted Green Line * A-Anchored (TriviaQA): Dash-Dot Orange Line * Q-Anchored (HotpotQA): Dash-Dot-Dot Red Line * A-Anchored (HotpotQA): Dotted-Dashed-Dashed Brown Line * Q-Anchored (NQ): Dashed Purple Line * A-Anchored (NQ): Dotted Gray Line ### Detailed Analysis **Left Graph (Mistral-7B-v0.1):** * **Q-Anchored (PopQA) - Solid Blue Line:** Starts near 0% accuracy, rapidly increases to approximately 80% by layer 10, and then fluctuates between 70% and 100% for the remaining layers. * **A-Anchored (PopQA) - Dashed Brown Line:** Starts around 60% accuracy, decreases to approximately 30% by layer 10, and then fluctuates between 30% and 40% for the remaining layers. * **Q-Anchored (TriviaQA) - Dotted Green Line:** Starts near 60% accuracy, decreases to approximately 40% by layer 10, and then fluctuates between 70% and 90% for the remaining layers. * **A-Anchored (TriviaQA) - Dash-Dot Orange Line:** Starts around 60% accuracy, decreases to approximately 30% by layer 10, and then fluctuates between 30% and 40% for the remaining layers. * **Q-Anchored (HotpotQA) - Dash-Dot-Dot Red Line:** Starts around 70% accuracy, decreases to approximately 20% by layer 10, and then fluctuates between 20% and 40% for the remaining layers. * **A-Anchored (HotpotQA) - Dotted-Dashed-Dashed Brown Line:** Starts around 60% accuracy, decreases to approximately 40% by layer 10, and then fluctuates between 40% and 50% for the remaining layers. * **Q-Anchored (NQ) - Dashed Purple Line:** Starts near 60% accuracy, increases to approximately 80% by layer 10, and then fluctuates between 70% and 100% for the remaining layers. * **A-Anchored (NQ) - Dotted Gray Line:** Starts around 60% accuracy, decreases to approximately 40% by layer 10, and then fluctuates between 40% and 50% for the remaining layers. **Right Graph (Mistral-7B-v0.3):** * **Q-Anchored (PopQA) - Solid Blue Line:** Starts near 0% accuracy, rapidly increases to approximately 80% by layer 10, and then fluctuates between 80% and 100% for the remaining layers. * **A-Anchored (PopQA) - Dashed Brown Line:** Starts around 60% accuracy, decreases to approximately 30% by layer 10, and then fluctuates between 30% and 40% for the remaining layers. * **Q-Anchored (TriviaQA) - Dotted Green Line:** Starts near 0% accuracy, increases to approximately 80% by layer 10, and then fluctuates between 80% and 100% for the remaining layers. * **A-Anchored (TriviaQA) - Dash-Dot Orange Line:** Starts around 60% accuracy, decreases to approximately 20% by layer 10, and then fluctuates between 20% and 40% for the remaining layers. * **Q-Anchored (HotpotQA) - Dash-Dot-Dot Red Line:** Starts around 60% accuracy, decreases to approximately 10% by layer 10, and then fluctuates between 10% and 30% for the remaining layers. * **A-Anchored (HotpotQA) - Dotted-Dashed-Dashed Brown Line:** Starts around 60% accuracy, decreases to approximately 30% by layer 10, and then fluctuates between 30% and 40% for the remaining layers. * **Q-Anchored (NQ) - Dashed Purple Line:** Starts near 60% accuracy, increases to approximately 80% by layer 10, and then fluctuates between 70% and 90% for the remaining layers. * **A-Anchored (NQ) - Dotted Gray Line:** Starts around 60% accuracy, decreases to approximately 40% by layer 10, and then fluctuates between 40% and 50% for the remaining layers. ### Key Observations * For both model versions, Q-Anchored approaches generally achieve higher accuracy than A-Anchored approaches after layer 10. * The accuracy of A-Anchored approaches tends to decrease in the initial layers before stabilizing. * The Q-Anchored (PopQA) and Q-Anchored (TriviaQA) datasets show a significant increase in accuracy after layer 5 for Mistral-7B-v0.3. * The performance on HotpotQA is generally lower compared to other datasets for both Q-Anchored and A-Anchored approaches. * The shaded regions around each line indicate the uncertainty or variance in the accuracy measurements. ### Interpretation The graphs suggest that the Mistral-7B models learn to answer questions more effectively as they process information through deeper layers. The difference in performance between Q-Anchored and A-Anchored approaches indicates that the way the question and answer are presented to the model significantly impacts its ability to provide accurate answers. The lower performance on HotpotQA suggests that this dataset, which requires more complex reasoning, is more challenging for the models. The improvement in Q-Anchored (PopQA) and Q-Anchored (TriviaQA) from v0.1 to v0.3 indicates that the newer version of the model has improved its ability to handle these specific question-answering tasks. The uncertainty regions highlight the variability in the model's performance, which could be due to factors such as the specific questions being asked or the training data used.

## Line Chart: Answer Accuracy vs. Layer for Mistral Models ### Overview The image presents two line charts, side-by-side, comparing the answer accuracy of the Mistral-7B-v0.1 and Mistral-7B-v0.3 models across different layers. The x-axis represents the layer number (from 0 to 30), and the y-axis represents the answer accuracy (from 0 to 100). Each chart displays multiple lines, each representing a different question-answering dataset and anchoring method. ### Components/Axes * **X-axis:** Layer (0 to 30, with tick marks at integer values) * **Y-axis:** Answer Accuracy (0 to 100, with tick marks at integer multiples of 20) * **Left Chart Title:** Mistral-7B-v0.1 * **Right Chart Title:** Mistral-7B-v0.3 * **Legend (Bottom-Left):** * Blue Solid Line: Q-Anchored (PopQA) * Orange Dashed Line: A-Anchored (PopQA) * Green Solid Line: Q-Anchored (TriviaQA) * Purple Solid Line: A-Anchored (TriviaQA) * Brown Dashed Line: Q-Anchored (HotpotQA) * Red Dashed Line: A-Anchored (HotpotQA) * Teal Solid Line: Q-Anchored (NQ) * Grey Solid Line: A-Anchored (NQ) ### Detailed Analysis or Content Details **Mistral-7B-v0.1 (Left Chart):** * **Q-Anchored (PopQA) - Blue Solid Line:** Starts at approximately 5% accuracy at layer 0, rises to a peak of around 95% at layer 6, then fluctuates between 50% and 90% for the remainder of the layers. * **A-Anchored (PopQA) - Orange Dashed Line:** Starts at approximately 55% accuracy at layer 0, decreases to around 30% by layer 5, and remains relatively stable between 20% and 40% for the rest of the layers. * **Q-Anchored (TriviaQA) - Green Solid Line:** Starts at approximately 0% accuracy at layer 0, rises rapidly to around 90% by layer 5, and fluctuates between 60% and 95% for the remaining layers. * **A-Anchored (TriviaQA) - Purple Solid Line:** Starts at approximately 20% accuracy at layer 0, rises to around 70% by layer 5, and fluctuates between 40% and 80% for the remaining layers. * **Q-Anchored (HotpotQA) - Brown Dashed Line:** Starts at approximately 0% accuracy at layer 0, rises to around 60% by layer 5, and fluctuates between 30% and 70% for the remaining layers. * **A-Anchored (HotpotQA) - Red Dashed Line:** Starts at approximately 20% accuracy at layer 0, rises to around 40% by layer 5, and remains relatively stable between 20% and 50% for the rest of the layers. * **Q-Anchored (NQ) - Teal Solid Line:** Starts at approximately 0% accuracy at layer 0, rises to around 80% by layer 5, and fluctuates between 50% and 90% for the remaining layers. * **A-Anchored (NQ) - Grey Solid Line:** Starts at approximately 20% accuracy at layer 0, rises to around 50% by layer 5, and fluctuates between 30% and 60% for the remaining layers. **Mistral-7B-v0.3 (Right Chart):** * **Q-Anchored (PopQA) - Blue Solid Line:** Starts at approximately 5% accuracy at layer 0, rises to a peak of around 95% at layer 6, then fluctuates between 50% and 90% for the remainder of the layers. * **A-Anchored (PopQA) - Orange Dashed Line:** Starts at approximately 55% accuracy at layer 0, decreases to around 30% by layer 5, and remains relatively stable between 20% and 40% for the rest of the layers. * **Q-Anchored (TriviaQA) - Green Solid Line:** Starts at approximately 0% accuracy at layer 0, rises rapidly to around 90% by layer 5, and fluctuates between 60% and 95% for the remaining layers. * **A-Anchored (TriviaQA) - Purple Solid Line:** Starts at approximately 20% accuracy at layer 0, rises to around 70% by layer 5, and fluctuates between 40% and 80% for the remaining layers. * **Q-Anchored (HotpotQA) - Brown Dashed Line:** Starts at approximately 0% accuracy at layer 0, rises to around 60% by layer 5, and fluctuates between 30% and 70% for the remaining layers. * **A-Anchored (HotpotQA) - Red Dashed Line:** Starts at approximately 20% accuracy at layer 0, rises to around 40% by layer 5, and remains relatively stable between 20% and 50% for the rest of the layers. * **Q-Anchored (NQ) - Teal Solid Line:** Starts at approximately 0% accuracy at layer 0, rises to around 80% by layer 5, and fluctuates between 50% and 90% for the remaining layers. * **A-Anchored (NQ) - Grey Solid Line:** Starts at approximately 20% accuracy at layer 0, rises to around 50% by layer 5, and fluctuates between 30% and 60% for the remaining layers. ### Key Observations * The Q-Anchored lines generally exhibit higher accuracy than the A-Anchored lines across all datasets and models. * Accuracy tends to increase rapidly in the initial layers (0-5) for most datasets. * After layer 5, the accuracy fluctuates significantly, suggesting instability or diminishing returns with increasing layers. * The two charts (v0.1 and v0.3) are nearly identical, indicating that the model update did not significantly alter the accuracy trends across layers and datasets. * PopQA and TriviaQA consistently show the highest accuracy, while HotpotQA and NQ show lower accuracy. ### Interpretation The data suggests that the Mistral models perform better when questions are used for anchoring (Q-Anchored) compared to answers (A-Anchored). The initial layers seem to be crucial for learning, as accuracy increases rapidly in this phase. However, beyond a certain point (around layer 5), adding more layers does not consistently improve accuracy and can even lead to fluctuations. The differences in accuracy across datasets indicate that the models are more proficient at answering questions from PopQA and TriviaQA than from HotpotQA and NQ. The similarity between the v0.1 and v0.3 models suggests that the update focused on areas other than the core accuracy trends observed in this analysis. The fluctuating accuracy after layer 5 could be due to overfitting, vanishing gradients, or the inherent complexity of the datasets. Further investigation is needed to understand the reasons behind these fluctuations and to identify strategies for improving the models' performance in the later layers.

## Line Charts: Mistral-7B Model Layer-wise Answer Accuracy ### Overview The image displays two side-by-side line charts comparing the layer-wise answer accuracy of two versions of the Mistral-7B language model (v0.1 and v0.3) across four different question-answering datasets. Each chart plots "Answer Accuracy" (y-axis) against the model's internal "Layer" number (x-axis) for two anchoring methods: "Q-Anchored" (question-anchored) and "A-Anchored" (answer-anchored). ### Components/Axes * **Chart Titles:** "Mistral-7B-v0.1" (left chart), "Mistral-7B-v0.3" (right chart). * **X-Axis:** Labeled "Layer". Scale runs from 0 to approximately 32, with major tick marks at 0, 10, 20, and 30. * **Y-Axis:** Labeled "Answer Accuracy". Scale runs from 0 to 100, with major tick marks at 0, 20, 40, 60, 80, and 100. * **Legend:** Positioned below both charts. It defines eight data series using a combination of color and line style: * **Q-Anchored Series (Solid Lines):** * Blue solid line: `Q-Anchored (PopQA)` * Green solid line: `Q-Anchored (TriviaQA)` * Purple solid line: `Q-Anchored (HotpotQA)` * Pink solid line: `Q-Anchored (NQ)` * **A-Anchored Series (Dashed/Dotted Lines):** * Orange dashed line: `A-Anchored (PopQA)` * Red dashed line: `A-Anchored (TriviaQA)` * Brown dashed line: `A-Anchored (HotpotQA)` * Gray dashed line: `A-Anchored (NQ)` ### Detailed Analysis **Chart 1: Mistral-7B-v0.1** * **Trend Verification:** The Q-Anchored (solid) lines generally show an initial rise, peak in the middle layers (approx. layers 8-20), and then exhibit high variance or decline in later layers. The A-Anchored (dashed) lines tend to start higher in early layers but show a more consistent downward trend as layer depth increases. * **Data Points (Approximate):** * **Q-Anchored (PopQA - Blue Solid):** Starts near 0% at layer 0, spikes to ~100% around layer 8, then fluctuates wildly between ~40% and ~100% for the remaining layers. * **Q-Anchored (TriviaQA - Green Solid):** Starts near 0%, rises to ~80% by layer 10, peaks near ~95% around layer 25, and ends near ~80% at layer 32. * **A-Anchored (PopQA - Orange Dashed):** Starts around ~60% at layer 0, gradually declines with fluctuations, ending near ~40% at layer 32. * **A-Anchored (TriviaQA - Red Dashed):** Starts around ~70%, declines steadily to ~20% by layer 20, and remains low. **Chart 2: Mistral-7B-v0.3** * **Trend Verification:** A significant shift is visible. The Q-Anchored (solid) lines rise sharply and reach high accuracy (>80%) by layer 10, maintaining high performance with less variance through the later layers. The A-Anchored (dashed) lines still show a declining trend but start from a lower initial point compared to v0.1. * **Data Points (Approximate):** * **Q-Anchored (PopQA - Blue Solid):** Rises steeply from ~0% to ~100% by layer 8, and remains consistently near or at 100% through layer 32. * **Q-Anchored (TriviaQA - Green Solid):** Follows a similar steep rise to ~90% by layer 10 and stays between ~85%-95% thereafter. * **A-Anchored (PopQA - Orange Dashed):** Starts around ~55%, declines to ~40% by layer 15, and fluctuates around 30-40% for later layers. * **A-Anchored (TriviaQA - Red Dashed):** Starts around ~65%, drops sharply to ~20% by layer 12, and remains very low (~10-20%). ### Key Observations 1. **Version Comparison:** Mistral-7B-v0.3 shows a dramatic improvement in the performance of Q-Anchored methods. They achieve high accuracy much earlier (by layer ~8-10) and sustain it, whereas in v0.1, performance was more volatile and peaked later. 2. **Anchoring Method Divergence:** Across both model versions, Q-Anchored methods consistently outperform A-Anchored methods in the middle and later layers. The gap between the two methods widens significantly in v0.3. 3. **Dataset Variability:** Performance varies by dataset. For example, in v0.3, `Q-Anchored (PopQA)` reaches a perfect 100% and stays there, while `Q-Anchored (HotpotQA)` (purple solid) shows more fluctuation between 60-90% in the later layers. 4. **Early Layer Behavior:** In both models, accuracy for most series is low in the very first layers (0-5), indicating the initial layers are not specialized for this task. ### Interpretation The data suggests a fundamental difference in how information is processed across the layers of the two model versions. The "Q-Anchored" approach, which likely measures the model's internal representation of the question, becomes a strong predictor of final answer accuracy early in the network of v0.3. This implies that v0.3 has developed more robust and task-relevant representations in its early-to-mid layers. Conversely, the declining trend of "A-Anchored" accuracy suggests that the direct representation of the answer becomes less determinative or is transformed as information flows through the network. The stark improvement from v0.1 to v0.3 indicates that the model update significantly enhanced the model's ability to encode and preserve question-relevant information through its processing depth, leading to more reliable performance. The persistent variability in datasets like HotpotQA (which involves multi-hop reasoning) highlights that complex reasoning remains a greater challenge even in the improved model.

## Line Graphs: Answer Accuracy Across Layers for Mistral-7B Models (v0.1 and v0.3) ### Overview The image contains two side-by-side line graphs comparing answer accuracy across transformer model layers (0–30) for two versions of the Mistral-7B model (v0.1 and v0.3). Each graph includes six data series representing different anchoring methods (Q-Anchored and A-Anchored) and datasets (PopQA, TriviaQA, HotpotQA, NQ). The graphs use color-coded lines with shaded confidence intervals. --- ### Components/Axes - **Y-Axis**: Answer Accuracy (%) - Range: 0–100% - Label: "Answer Accuracy" - **X-Axis**: Layer - Range: 0–30 - Label: "Layer" - **Legends**: - **Left Graph (v0.1)**: - Q-Anchored (PopQA): Solid blue - A-Anchored (PopQA): Dashed orange - Q-Anchored (TriviaQA): Solid green - A-Anchored (TriviaQA): Dashed brown - **Right Graph (v0.3)**: - Q-Anchored (HotpotQA): Solid purple - A-Anchored (HotpotQA): Dashed gray - Q-Anchored (NQ): Solid pink - A-Anchored (NQ): Dashed red --- ### Detailed Analysis #### Left Graph (Mistral-7B-v0.1) 1. **Q-Anchored (PopQA)** (Solid Blue): - Starts at ~80% accuracy at layer 0, drops sharply to ~20% by layer 5, then fluctuates between 30–70% with peaks at layers 10, 15, and 25. 2. **A-Anchored (PopQA)** (Dashed Orange): - Starts at ~60%, dips to ~40% by layer 10, then stabilizes between 40–60% with minor oscillations. 3. **Q-Anchored (TriviaQA)** (Solid Green): - Begins at ~70%, plunges to ~10% by layer 5, then oscillates between 20–60% with a peak at layer 20. 4. **A-Anchored (TriviaQA)** (Dashed Brown): - Starts at ~50%, drops to ~30% by layer 10, then fluctuates between 30–50% with a peak at layer 25. #### Right Graph (Mistral-7B-v0.3) 1. **Q-Anchored (HotpotQA)** (Solid Purple): - Starts at ~70%, peaks at ~90% by layer 10, then declines to ~60% by layer 30 with minor fluctuations. 2. **A-Anchored (HotpotQA)** (Dashed Gray): - Starts at ~50%, rises to ~70% by layer 15, then stabilizes between 60–70% with slight dips. 3. **Q-Anchored (NQ)** (Solid Pink): - Begins at ~60%, drops to ~40% by layer 10, then fluctuates between 30–60% with a peak at layer 25. 4. **A-Anchored (NQ)** (Dashed Red): - Starts at ~40%, rises to ~60% by layer 20, then declines to ~40% by layer 30 with oscillations. --- ### Key Observations 1. **Model Version Differences**: - v0.3 shows smoother trends and higher overall accuracy compared to v0.1, which exhibits sharper fluctuations. 2. **Dataset-Specific Performance**: - **HotpotQA** (v0.3) achieves the highest peak accuracy (~90%) among all datasets. - **NQ** (v0.3) shows the most erratic behavior, with a sharp drop at layer 10. 3. **Anchoring Method Trends**: - Q-Anchored methods generally outperform A-Anchored in v0.3 but underperform in v0.1 for PopQA and TriviaQA. - A-Anchored methods in v0.1 (e.g., PopQA) exhibit more stability but lower peaks. --- ### Interpretation The data suggests that model version v0.3 improves stability and accuracy across layers compared to v0.1. Q-Anchored methods perform better for HotpotQA and NQ in v0.3, while A-Anchored methods show resilience in v0.1 for PopQA and TriviaQA. The sharp dips in v0.1 (e.g., Q-Anchored TriviaQA at layer 5) may indicate architectural instability in early layers, whereas v0.3’s smoother curves suggest refined training or architecture. The dataset-specific performance highlights the importance of anchoring strategies tailored to question types (e.g., HotpotQA’s reliance on Q-Anchored methods).