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lower mAP #78
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config.yaml 内容如下: AUTO_RESUME: true DATASET:
LOSS:
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hello,I modified the config xxx.py file into a yaml file and used the hrnet or higherhrnet framework code for training. I found that the mAP on the coco validation dataset was only about 0.51.
2022-08-22 15:25:59,519 Epoch: [179][0/2341] Time 3.316s (3.316s) Speed 19.3 samples/s Data 2.263s (2.263s) Loss 0.00042 (0.00042) Accuracy 0.751 (0.751)
2022-08-22 15:30:13,151 Epoch: [179][300/2341] Time 0.813s (0.854s) Speed 78.8 samples/s Data 0.000s (0.019s) Loss 0.00032 (0.00038) Accuracy 0.803 (0.748)
2022-08-22 15:34:33,721 Epoch: [179][600/2341] Time 0.813s (0.861s) Speed 78.7 samples/s Data 0.000s (0.014s) Loss 0.00039 (0.00038) Accuracy 0.725 (0.747)
2022-08-22 15:42:29,909 Epoch: [179][900/2341] Time 1.648s (1.103s) Speed 38.8 samples/s Data 0.000s (0.012s) Loss 0.00035 (0.00038) Accuracy 0.737 (0.746)
2022-08-22 15:50:49,289 Epoch: [179][1200/2341] Time 1.665s (1.243s) Speed 38.4 samples/s Data 0.000s (0.013s) Loss 0.00035 (0.00038) Accuracy 0.756 (0.747)
2022-08-22 15:59:08,989 Epoch: [179][1500/2341] Time 1.639s (1.328s) Speed 39.1 samples/s Data 0.000s (0.013s) Loss 0.00035 (0.00038) Accuracy 0.775 (0.747)
2022-08-22 16:07:28,549 Epoch: [179][1800/2341] Time 1.668s (1.384s) Speed 38.4 samples/s Data 0.000s (0.013s) Loss 0.00041 (0.00038) Accuracy 0.752 (0.748)
2022-08-22 16:15:47,927 Epoch: [179][2100/2341] Time 1.674s (1.424s) Speed 38.2 samples/s Data 0.000s (0.012s) Loss 0.00033 (0.00038) Accuracy 0.785 (0.748)
2022-08-22 16:22:31,716 Test: [0/199] Time 1.750 (1.750) Loss 0.0004 (0.0004) Accuracy 0.816 (0.816)
2022-08-22 16:24:33,818 => writing results json to LiteHRNet_w18_output/coco/HigherLiteHRNet/LiteHRNet_w18_256x256_coco_correct_lr1e-3/results/keypoints_val2017_results_0.json
2022-08-22 16:24:44,456 | Arch | AP | Ap .5 | AP .75 | AP (M) | AP (L) | AR | AR .5 | AR .75 | AR (M) | AR (L) |
2022-08-22 16:24:44,457 |---|---|---|---|---|---|---|---|---|---|---|
2022-08-22 16:24:44,457 | HigherLiteHRNet | 0.511 | 0.807 | 0.544 | 0.501 | 0.530 | 0.557 | 0.830 | 0.598 | 0.539 | 0.583 |
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