Comments (2)
I provide the first 20 epochs' accuracy from the training logger.
Both models should have the same performance because the weight should be equivalent. I have checked my model, using a random input and random weight. You can try it by yourself. Model output should be same.
mobileone_s0, epoch 0, acc 11.02199935913086
mobileone_s0, epoch 1, acc 25.20800018310547
mobileone_s0, epoch 2, acc 34.14400100708008
mobileone_s0, epoch 3, acc 39.06599807739258
mobileone_s0, epoch 4, acc 40.4839973449707
mobileone_s0, epoch 5, acc 42.15599822998047
mobileone_s0, epoch 6, acc 44.534000396728516
mobileone_s0, epoch 7, acc 44.3120002746582
mobileone_s0, epoch 8, acc 46.37199783325195
mobileone_s0, epoch 9, acc 45.077999114990234
mobileone_s0, epoch 10, acc 47.44599914550781
mobileone_s0, epoch 11, acc 48.06999969482422
mobileone_s0, epoch 12, acc 48.4119987487793
mobileone_s0, epoch 13, acc 47.77399826049805
mobileone_s0, epoch 14, acc 48.70399856567383
mobileone_s0, epoch 15, acc 50.86399841308594
mobileone_s0, epoch 16, acc 40.395999908447266
mobileone_s0, epoch 17, acc 50.52399826049805
mobileone_s0, epoch 18, acc 48.99399948120117
mobileone_s0, epoch 19, acc 50.77799987792969
mobileone_s0, epoch 20, acc 49.92399978637695
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Thank you very much for your reply
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Related Issues (15)
- Could not get your pretrained weights on google drive disk! HOT 1
- How did you check the model and depolyment model results consistency HOT 5
- add ‘SeBlock’ can't work ? HOT 2
- why use normal stem for self.stage0? HOT 2
- 推理速度 HOT 1
- repvgg_model_convert function should't have the "x", please confirm it HOT 3
- why the acc is different between before and after merging blocks HOT 1
- [BUG] Skip connection should be always added to DW branches. HOT 2
- Could you please provide dataset format? HOT 2
- Hi~How about quantization? Is quantization all good? HOT 2
- About mobileone_s2 HOT 1
- Can you privide the checkpoint about the make_mobileone_s0 HOT 1
- question about merge conv and bn HOT 2
- reparameterize requestion
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