Update README.md

README.md

@@ -77,14 +77,13 @@ print(generated_text)
 
 ## Results
 
-Below, we present  the performance of **LlamaLens** , where *"English"* refers to the English-instructed model and *"Native"* refers to the model trained with native language instructions compared to existing SOTA (if available) and the Llama-Instruct baseline, The “Δ” (Delta) column here is 
-calculated as **(LLamalens – SOTA)**.
+Below, we present  the performance of **L-Lens: LlamaLens** , where *"Eng"* refers to the English-instructed model and *"Native"* refers to the model trained with native language instructions. The results are compared against the SOTA (where available) and the Base: **Llama-Instruct 3.1 baseline**. The **Δ** (Delta) column indicates the difference between LlamaLens and the SOTA performance, calculated as (LlamaLens – SOTA).
 
 ---
 
 ## Arabic
 
-|              **Task**              |                  **Dataset**                 | **Metric** | **SOTA** | **Llama3.1-instruct** | **Llamalens-English** | **Llamalens-Native** | **Δ (LLamalens - SOTA)** |
+|              **Task**              |                  **Dataset**                 | **Metric** | **SOTA** | **Base** | **L-Lens-Eng** | **L-Lens-Native** | **Δ (L-Lens (Eng) - SOTA)** |
 |:----------------------------------:|:--------------------------------------------:|:----------:|:--------:|:---------------------:|:---------------------:|:--------------------:|:------------------------:|
 |    Attentionworthiness Detection   |              CT22Attentionworthy             |    W-F1    |   0.412  |         0.158         |         0.425         |         0.454        |           0.013          |
 |      Checkworthiness Detection     |               CT24_checkworthy               |   F1_Pos   |   0.569  |         0.610         |         0.502         |         0.509        |          -0.067          |