Update README.md
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README.md
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@@ -58,7 +58,7 @@ InternVL 2.0 is a multimodal large language model series, featuring models of va
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| SEED-Image | 77.1 | - | 78.2 | 78.2 |
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| HallBench<sub>avg</sub> | 55.0 | 49.9 | 56.9 | 55.2 |
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| MathVista<sub>testmini</sub> | 63.8 | 67.7 | 63.7 | 65.5 |
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| OpenCompass<sub>avg</sub> | 69.9 | 67.9 | 69.7 |
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- 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. OCRBench, RealWorldQA, HallBench, and MathVista were evaluated using the VLMEvalKit.
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@@ -478,7 +478,7 @@ InternVL 2.0 是一个多模态大语言模型系列,包含各种规模的模
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| SEED-Image | 77.1 | - | 78.2 | 78.2 |
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| HallBench<sub>avg</sub> | 55.0 | 49.9 | 56.9 | 55.2 |
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| MathVista<sub>testmini</sub> | 63.8 | 67.7 | 63.7 | 65.5 |
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| OpenCompass<sub>avg</sub> | 69.9 | 67.9 | 69.7 |
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- 我们同时使用 InternVL 和 VLMEvalKit 仓库进行模型评估。具体来说,DocVQA、ChartQA、InfoVQA、TextVQA、MME、AI2D、MMBench、CCBench、MMVet 和 SEED-Image 的结果是使用 InternVL 仓库测试的。OCRBench、RealWorldQA、HallBench 和 MathVista 是使用 VLMEvalKit 进行评估的。
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| SEED-Image | 77.1 | - | 78.2 | 78.2 |
|
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| HallBench<sub>avg</sub> | 55.0 | 49.9 | 56.9 | 55.2 |
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| MathVista<sub>testmini</sub> | 63.8 | 67.7 | 63.7 | 65.5 |
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+
| OpenCompass<sub>avg</sub> | 69.9 | 67.9 | 69.7 | 71.0 |
|
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|
63 |
- 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. OCRBench, RealWorldQA, HallBench, and MathVista were evaluated using the VLMEvalKit.
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|
478 |
| SEED-Image | 77.1 | - | 78.2 | 78.2 |
|
479 |
| HallBench<sub>avg</sub> | 55.0 | 49.9 | 56.9 | 55.2 |
|
480 |
| MathVista<sub>testmini</sub> | 63.8 | 67.7 | 63.7 | 65.5 |
|
481 |
+
| OpenCompass<sub>avg</sub> | 69.9 | 67.9 | 69.7 | 71.0 |
|
482 |
|
483 |
- 我们同时使用 InternVL 和 VLMEvalKit 仓库进行模型评估。具体来说,DocVQA、ChartQA、InfoVQA、TextVQA、MME、AI2D、MMBench、CCBench、MMVet 和 SEED-Image 的结果是使用 InternVL 仓库测试的。OCRBench、RealWorldQA、HallBench 和 MathVista 是使用 VLMEvalKit 进行评估的。
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484 |
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