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How to Evaluate InternVL-Chat-V1-5 using VLMEvalKit?

In this tutorial, we will provide a detailed guide on how to evaluate InternVL-Chat-V1-5 using VLMEvalKit.

First of all, please follow this guide to install VLMEvalKit.

MMBench_DEV_EN

torchrun --nproc-per-node=8 run.py --data MMBench_DEV_EN --model InternVL-Chat-V1-5 --verbose

The result is:

2024-04-29 18:24:58,395 - Evaluation - INFO -   split   Overall  ...  spatial_relationship  structuralized_imagetext_understanding
0   dev  0.808419  ...              0.422222                                0.628205

MMBench_DEV_CN

torchrun --nproc-per-node=8 run.py --data MMBench_DEV_CN --model InternVL-Chat-V1-5 --verbose

The result is:

2024-04-29 18:26:05,209 - Evaluation - INFO -   split   Overall  ...  spatial_relationship  structuralized_imagetext_understanding
0   dev  0.803265  ...              0.377778                                0.615385

MMStar

torchrun --nproc-per-node=8 run.py --data MMStar --model InternVL-Chat-V1-5 --verbose

The result is:

2024-04-29 18:21:56,491 - Evaluation - INFO -   split   Overall  ...   math  science & technology
0  none  0.572667  ...  0.564                 0.408

MME

torchrun --nproc-per-node=8 run.py --data MME --model InternVL-Chat-V1-5 --verbose

The result is:

2024-04-29 18:42:43,864 - Evaluation - INFO - Score:
2024-04-29 18:42:43,864 - Evaluation - INFO -     perception   reasoning    OCR  ...     posters  scene  text_translation
0  1641.915766  519.642857  147.5  ...  171.768707  156.5             185.0

SEEDBench_IMG

torchrun --nproc-per-node=8 run.py --data SEEDBench_IMG --model InternVL-Chat-V1-5 --verbose

The result is:

2024-04-29 18:58:54,973 - Evaluation - INFO - Score:
2024-04-29 18:58:54,973 - Evaluation - INFO -   split   Overall  ...  Text Understanding  Visual Reasoning
0  none  0.757167  ...            0.440476          0.806647

MMVet

torchrun --nproc-per-node=8 run.py --data MMVet --model InternVL-Chat-V1-5 --verbose

The result is:

2024-04-29 18:32:38,748 - Evaluation - INFO - Score:
2024-04-29 18:32:38,748 - Evaluation - INFO -   Category  tot        acc
0      rec  187  61.818182
1      ocr  108  68.981481
2     know   84  46.428571
3      gen   80  44.875000
4     spat   75  63.600000
5     math   26  62.307692
6  Overall  218  61.513761

Note that because the version of GPT used for scoring differs from the official server, the scores tested by VLMEvalKit will be slightly different.

MMMU_DEV_VAL

torchrun --nproc-per-node=8 run.py --data MMMU_DEV_VAL --model InternVL-Chat-V1-5 --verbose

The result is:

2024-04-29 18:20:04,977 - Evaluation - INFO -         split  Overall  ...  Science  Tech & Engineering
0         dev     0.48  ...     0.36            0.428571
1  validation     0.45  ...     0.38            0.371429

MathVista_MINI

torchrun --nproc-per-node=8 run.py --data MathVista_MINI --model InternVL-Chat-V1-5 --verbose

The result is:

2024-04-29 18:39:25,736 - Evaluation - INFO -                      Task&Skill   tot  prefetch  hit  prefetch_rate        acc
0                       Overall  1000       545  521      54.500000  52.100000
1          scientific reasoning   122        89   70      72.950820  57.377049
2   textbook question answering   158       101   86      63.924051  54.430380
3           numeric commonsense   144        39   41      27.083333  28.472222
4          arithmetic reasoning   353       147  198      41.643059  56.090652
5     visual question answering   179        91   88      50.837989  49.162011
6            geometry reasoning   239       144   94      60.251046  39.330544
7           algebraic reasoning   281       170  109      60.498221  38.790036
8      geometry problem solving   208       135   79      64.903846  37.980769
9             math word problem   186        70  118      37.634409  63.440860
10            logical reasoning    37        18    5      48.648649  13.513514
11    figure question answering   269       148  150      55.018587  55.762082
12        statistical reasoning   301       143  196      47.508306  65.116279

Note that because the version of GPT used for answer extraction differs from the official code, the scores tested by VLMEvalKit will be slightly different.

ScienceQA_TEST

torchrun --nproc-per-node=8 run.py --data ScienceQA_TEST --model InternVL-Chat-V1-5 --verbose

The result is:

2024-04-29 19:10:03,279 - Evaluation - INFO - Score:
2024-04-29 19:10:03,279 - Evaluation - INFO -   split   Overall  ...  Weather and climate  World religions
0  test  0.940506  ...             0.948276              1.0

HallusionBench

torchrun --nproc-per-node=8 run.py --data HallusionBench --model InternVL-Chat-V1-5 --verbose

The result is:

2024-04-29 18:21:37,606 - Evaluation - INFO - Score:
2024-04-29 18:21:37,606 - Evaluation - INFO -           split       aAcc       fAcc       qAcc
0       Overall  66.771819  40.173410  40.879121
1            VS  71.944444  40.517241  51.123596
2            VD  63.620981  40.000000  34.296029
3        VS_ocr  59.259259  38.461538  22.222222
4      VD_video  51.176471  10.416667  13.043478
5        VS_map  56.250000  18.181818  18.750000
6      VS_chart  81.538462  50.000000  72.368421
7      VS_table  75.892857  46.428571  55.813953
8     VD_figure  77.500000  65.853659  53.846154
9   VD_illusion  66.666667  41.935484  34.722222
10      VD_math  56.481481  25.000000  27.777778
11       VD_ocr  78.651685  58.139535  58.139535

TextVQA_VAL

torchrun --nproc-per-node=8 run.py --data TextVQA_VAL --model InternVL-Chat-V1-5 --verbose

The result is:

2024-04-29 18:41:32,873 - Evaluation - INFO - VQA Eval Finished. Saved to ./InternVL-Chat-V1-5/InternVL-Chat-V1-5_TextVQA_VAL_acc.csv.
2024-04-29 18:41:32,873 - Evaluation - INFO -    Overall
0   80.488

ChartQA_TEST

torchrun --nproc-per-node=8 run.py --data ChartQA_TEST --model InternVL-Chat-V1-5 --verbose

The result is:

2024-04-29 18:44:05,458 - Evaluation - INFO - VQA Eval Finished. Saved to ./InternVL-Chat-V1-5/InternVL-Chat-V1-5_ChartQA_TEST_acc.csv.
2024-04-29 18:44:05,458 - Evaluation - INFO -    test_human  test_augmented  Overall
0       73.04           94.32    83.68

AI2D_TEST

torchrun --nproc-per-node=8 run.py --data AI2D_TEST --model InternVL-Chat-V1-5 --verbose

The result is:

2024-04-29 19:02:17,402 - Evaluation - INFO - Score:
2024-04-29 19:02:17,402 - Evaluation - INFO -   split   Overall  atomStructure  ...   typesOf  volcano  waterCNPCycle
0  none  0.806995           0.75  ...  0.752187      1.0       0.727273

LLaVABench

torchrun --nproc-per-node=8 run.py --data LLaVABench --model InternVL-Chat-V1-5 --verbose

The result is:

Processing ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 0:00:00 60/60 100%
     split  Relative Score (main)  VLM Score  GPT4 Score
0  overall                   82.0       63.7        77.7
1     conv                   82.9       74.1        89.4
2   detail                   72.0       48.0        66.7
3  complex                   86.0       65.7        76.4

DocVQA_VAL

torchrun --nproc-per-node=8 run.py --data DocVQA_VAL --model InternVL-Chat-V1-5 --verbose

The result is:

2024-04-29 19:18:54,661 - Evaluation - INFO - VQA Eval Finished. Saved to ./InternVL-Chat-V1-5/InternVL-Chat-V1-5_DocVQA_VAL_acc.csv.
2024-04-29 19:18:54,661 - Evaluation - INFO -          val    Overall
0  90.500323  90.500323

InfoVQA_VAL

torchrun --nproc-per-node=8 run.py --data DocVQA_VAL --model InternVL-Chat-V1-5 --verbose

The result is:

2024-04-29 18:44:50,851 - Evaluation - INFO - VQA Eval Finished. Saved to ./InternVL-Chat-V1-5/InternVL-Chat-V1-5_InfoVQA_VAL_acc.csv.
2024-04-29 18:44:50,851 - Evaluation - INFO -          val    Overall
0  71.920408  71.920408

OCRBench

torchrun --nproc-per-node=8 run.py --data DocVQA_VAL --model InternVL-Chat-V1-5 --verbose

The result is:

2024-04-29 18:56:05,437 - Evaluation - INFO - Score:
2024-04-29 18:56:05,437 - Evaluation - INFO - Text Recognition:238
2024-04-29 18:56:05,437 - Evaluation - INFO - Scene Text-centric VQA:178
2024-04-29 18:56:05,437 - Evaluation - INFO - Doc-oriented VQA:151
2024-04-29 18:56:05,438 - Evaluation - INFO - Key Information Extraction:153
2024-04-29 18:56:05,438 - Evaluation - INFO - Handwritten Mathematical Expression Recognition:4
2024-04-29 18:56:05,438 - Evaluation - INFO - Final Score:724
2024-04-29 18:56:05,438 - Evaluation - INFO - Final Score Norm:72.4

RealWorldQA

torchrun --nproc-per-node=8 run.py --data RealWorldQA --model InternVL-Chat-V1-5 --verbose

The result is:

2024-04-29 18:56:43,192 - Evaluation - INFO - Score:
2024-04-29 18:56:43,192 - Evaluation - INFO -   split   Overall
0  none  0.660131