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README.md

@@ -25,15 +25,15 @@ InternVL2 is a multimodal large language model series, featuring models of vario
 
 |          Benchmark           | MiniCPM-Llama3-V-2_5 | InternVL2-8B |
 | :--------------------------: | :------------------: | :----------: |
-|          Model Size          |         8.5B         |              |
+|          Model Size          |         8.5B         |     8.1B     |
 |                              |                      |              |
-|    DocVQA<sub>test</sub>     |         84.8         |     TODO     |
+|    DocVQA<sub>test</sub>     |         84.8         |     91.6     |
 |    ChartQA<sub>test</sub>    |          -           |     83.3     |
-|    InfoVQA<sub>test</sub>    |          -           |     TODO     |
+|    InfoVQA<sub>test</sub>    |          -           |     74.8     |
 |    TextVQA<sub>val</sub>     |         76.6         |     77.4     |
-|           OCRBench           |         725          |     TODO     |
+|           OCRBench           |         725          |     794      |
 |      MME<sub>sum</sub>       |        2024.6        |    2210.3    |
-|         RealWorldQA          |         63.5         |              |
+|         RealWorldQA          |         63.5         |     64.4     |
 |     AI2D<sub>test</sub>      |         78.4         |     83.8     |
 |      MMMU<sub>val</sub>      |         45.8         |     49.3     |
 |  MMBench-EN<sub>test</sub>   |         77.2         |     81.7     |
@@ -41,8 +41,8 @@ InternVL2 is a multimodal large language model series, featuring models of vario
 |    CCBench<sub>dev</sub>     |         45.9         |     75.9     |
 |  MMVet<sub>GPT-4-0613</sub>  |          -           |     60.0     |
 |          SEED-Image          |         72.3         |     76.2     |
-|   HallBench<sub>avg</sub>    |         42.4         |              |
-| MathVista<sub>testmini</sub> |         54.3         |              |
+|   HallBench<sub>avg</sub>    |         42.4         |     45.2     |
+| MathVista<sub>testmini</sub> |         54.3         |     58.3     |
 
 - We simultaneously use InternVL and VLMEvalKit repositories for model evaluation. Specifically, the results reported for DocVQA, ChartQA, InfoVQA, TextVQA, MME, AI2D, MMBench, CCBench, MMVet, and SEED-Image were tested using the InternVL repository. MMMU, OCRBench, RealWorldQA, HallBench, and MathVista were evaluated using the VLMEvalKit.