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Data Purchasing Challenge 2022

[LB 0.880] My Experiment Results + Baseline too I guess 😬

Experiment Results

leocd

 

 

 

EXPERIMENT RESULTS

This is my experiment results.

I'm using this same parameter for each experiment :

  • model : efficienet-b1
  • input: raw image
  • epoch: 20
  • optim: Adam

And here's the results :

exp no. augmentation pretrained purchase_method score_pretraining_phase score_purchase_phase score_validation_phase LB_Score
1 NO NO NO 0.773 0.773 0.760
2 NO NO RANDOM 3000 0.773 0.804 0.760
3 NO NO ALL 10000 0.773 0.841 0.835
4 NO YES NO 0.857 0.857 0.850
5 NO YES RANDOM 3000 0.857 0.864 0.845 0.851
6 NO YES ALL 10000 0.857 0.892 0.875
7 YES YES NO 0.868 0.868 0.865
8 YES YES RANDOM 3000 0.868 0.886 0.869 0.880
9 YES YES ALL 10000 0.868 0.902 0.893

Conclusions :

  • Use pretrained weight
  • Use augmentation
  • Smart purchase increase the score

Notebook Link :

No Augmentation, No Pretrained, No Purchase : LINK

No Augmentation, No Pretrained, Random 3000 Purchase : LINK

No Augmentation, No Pretrained, Full 10000 Purchase : LINK

No Augmentation, Pretrained, Random 3000 Purchase : LINK

No Augmentation, Pretrained, Full 10000 Purchase : LINK

Augmentation, Pretrained, Random 3000 Purchase (GITLAB) : LINK

Augmentation, Pretrained, Full 10000 Purchase : LINK

Pls leave some 💖 thanks!

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