Update README_en.md

README_en.md

@@ -22,12 +22,14 @@ Evaluation results from [Nejumi LLM Leaderboard 3 (W&B)](https://wandb.ai/wandb-
 Blue: Original
 Orange: 8bit
 Green: 4bit
+
 ### Benchmark Overall Results
 | Model | GLP Average | ALT Average | Overall Average |
 |--------|---------|---------|----------|
 | phi-4 Int4 | 0.5815 | 0.6953 | 0.6384 |
 | phi-4 Int8 | 0.5948 | 0.7015 | 0.6482 |
 | phi-4 Original | 0.5950 | 0.7005 | 0.6477 |
+
 ### General Language Performance (GLP) Details
 | Subcategory | Int4 | Int8 | Original |
 |-------------|------|------|------|
@@ -38,9 +40,12 @@ Green: 4bit
 | Mathematical Reasoning | 0.5400 | 0.5967 | 0.5817 |
 | Extraction | 0.3304 | 0.3408 | 0.3470 |
 | Knowledge & QA | 0.5587 | 0.5735 | 0.5685 |
-| English | 0.3035 | 0.2351 | 0.2158 |
+| MMLU_en | 0.3035 | 0.2351 | 0.2158 |
 | Semantic Analysis | 0.4220 | 0.5200 | 0.5070 |
 | Syntax Analysis | 0.4399 | 0.4967 | 0.4903 |
+
+Note: The low MMLU_en scores are due to the model's inability to strictly follow the required answer format for this benchmark, rather than reflecting its actual knowledge or reasoning capabilities.
+
 ### Alignment (ALT) Details
 | Subcategory | Int4 | Int8 | Original |
 |-------------|------|------|------|
@@ -50,6 +55,7 @@ Green: 4bit
 | Bias | 0.8858 | 0.8730 | 0.8650 |
 | Robustness | 0.3717 | 0.4208 | 0.4226 |
 | Truthfulness | 0.5292 | 0.4983 | 0.5206 |
+
 ### Benchmark Scores
 | Benchmark | Int4 | Int8 | Original |
 |-------------|------|------|------|
@@ -57,6 +63,7 @@ Green: 4bit
 | JASTER (2-shot) | 0.6136 | 0.6441 | 0.6398 |
 | MT-Bench | 8.2438 | 8.2000 | 8.1313 |
 | LCTG | 0.6860 | 0.6670 | 0.6750 |
+
 ---
 ## Model Characteristics & Evaluation
 - **High Stability**: Standard GPTQ quantization achieves sufficient performance for 14B class models