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Different features

Different features

Andrew
Created on November 2|Last edited on November 2

Features Compare




Select runs that logged learner_prob-byol_r50-e3b0c442.pth_feat1.npy/all/top1
to visualize data in this line chart.
Select runs that logged learner_prob-byol_r50-e3b0c442.pth_feat1.npy/all/ece
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Showing first 10 runs
0500m11.5cost-per-image0.060.070.080.090.10.2
11-02-20-bayes-linear_nn-learner.features_moco-learner.early_stop_val-n_prototype_data_per_class_5-prototype_noise_0.2-optimizer.algo_LearnerInEM+PseudoLabel+UpdateEnd
11-02-20-bayes-linear_nn-learner.features_moco-learner.early_stop_approx_all-n_prototype_data_per_class_5-prototype_noise_0.2-optimizer.algo_LearnerInEM+PseudoLabel+UpdateEnd
11-02-20-bayes-linear_nn-learner.features_moco-learner.early_stop_val-n_prototype_data_per_class_5-prototype_noise_0.2-optimizer.algo_Lean+LearnerInEM+PseudoLabel+UpdateEnd
11-02-20-bayes-linear_nn-learner.features_moco-learner.early_stop_approx_all-n_prototype_data_per_class_10-prototype_noise_0.0-optimizer.algo_LearnerInEM+PseudoLabel+UpdateEnd
11-02-20-bayes-linear_nn-learner.features_moco-learner.early_stop_approx_all-n_prototype_data_per_class_5-prototype_noise_0.0-optimizer.algo_LearnerInEM+PseudoLabel+UpdateEnd
11-02-20-bayes-linear_nn-learner.features_moco-learner.early_stop_approx_all-n_prototype_data_per_class_10-prototype_noise_0.2-optimizer.algo_Lean+LearnerInEM+PseudoLabel+UpdateEnd
11-02-20-bayes-linear_nn-learner.features_moco-learner.early_stop_approx_all-n_prototype_data_per_class_10-prototype_noise_0.2-optimizer.algo_LearnerInEM+PseudoLabel+UpdateEnd
11-02-20-bayes-linear_nn-learner.features_moco-learner.early_stop_approx_all-n_prototype_data_per_class_5-prototype_noise_0.2-optimizer.algo_Lean+LearnerInEM+PseudoLabel+UpdateEnd
11-02-20-bayes-linear_nn-learner.features_moco-learner.early_stop_approx_all-n_prototype_data_per_class_5-prototype_noise_0.0-optimizer.algo_Lean+LearnerInEM+PseudoLabel+UpdateEnd
11-02-20-bayes-linear_nn-learner.features_moco-learner.early_stop_val-n_prototype_data_per_class_10-prototype_noise_0.2-optimizer.algo_Lean+LearnerInEM+PseudoLabel+UpdateEnd
0500m11.5cost-per-image05000100001500020000
11-02-20-bayes-linear_nn-learner.features_moco-learner.early_stop_val-n_prototype_data_per_class_5-prototype_noise_0.2-optimizer.algo_LearnerInEM+PseudoLabel+UpdateEnd
11-02-20-bayes-linear_nn-learner.features_moco-learner.early_stop_approx_all-n_prototype_data_per_class_5-prototype_noise_0.2-optimizer.algo_LearnerInEM+PseudoLabel+UpdateEnd
11-02-20-bayes-linear_nn-learner.features_moco-learner.early_stop_val-n_prototype_data_per_class_5-prototype_noise_0.2-optimizer.algo_Lean+LearnerInEM+PseudoLabel+UpdateEnd
11-02-20-bayes-linear_nn-learner.features_moco-learner.early_stop_approx_all-n_prototype_data_per_class_10-prototype_noise_0.0-optimizer.algo_LearnerInEM+PseudoLabel+UpdateEnd
11-02-20-bayes-linear_nn-learner.features_moco-learner.early_stop_approx_all-n_prototype_data_per_class_5-prototype_noise_0.0-optimizer.algo_LearnerInEM+PseudoLabel+UpdateEnd
11-02-20-bayes-linear_nn-learner.features_moco-learner.early_stop_approx_all-n_prototype_data_per_class_10-prototype_noise_0.2-optimizer.algo_Lean+LearnerInEM+PseudoLabel+UpdateEnd
11-02-20-bayes-linear_nn-learner.features_moco-learner.early_stop_approx_all-n_prototype_data_per_class_10-prototype_noise_0.2-optimizer.algo_LearnerInEM+PseudoLabel+UpdateEnd
11-02-20-bayes-linear_nn-learner.features_moco-learner.early_stop_approx_all-n_prototype_data_per_class_5-prototype_noise_0.2-optimizer.algo_Lean+LearnerInEM+PseudoLabel+UpdateEnd
11-02-20-bayes-linear_nn-learner.features_moco-learner.early_stop_approx_all-n_prototype_data_per_class_5-prototype_noise_0.0-optimizer.algo_Lean+LearnerInEM+PseudoLabel+UpdateEnd
11-02-20-bayes-linear_nn-learner.features_moco-learner.early_stop_val-n_prototype_data_per_class_10-prototype_noise_0.2-optimizer.algo_Lean+LearnerInEM+PseudoLabel+UpdateEnd
11-02-20-bayes-linear_nn-learner.features_moco-learner.early_stop_val-n_prototype_data_per_class_10-prototype_noise_0.2-optimizer.algo_LearnerInEM+PseudoLabel+UpdateEnd
11-02-20-bayes-linear_nn-learner.features_moco-learner.early_stop_val-n_prototype_data_per_class_5-prototype_noise_0.0-optimizer.algo_LearnerInEM+PseudoLabel+UpdateEnd
11-02-20-bayes-linear_nn-learner.features_moco-learner.early_stop_val-n_prototype_data_per_class_10-prototype_noise_0.0-optimizer.algo_LearnerInEM+PseudoLabel+UpdateEnd
11-02-20-bayes-linear_nn-learner.features_moco-learner.early_stop_approx_all-n_prototype_data_per_class_10-prototype_noise_0.0-optimizer.algo_Lean+LearnerInEM+PseudoLabel+UpdateEnd
11-02-20-bayes-linear_nn-learner.features_moco-learner.early_stop_val-n_prototype_data_per_class_5-prototype_noise_0.0-optimizer.algo_Lean+LearnerInEM+PseudoLabel+UpdateEnd
11-02-20-bayes-linear_nn-learner.features_moco-learner.early_stop_val-n_prototype_data_per_class_10-prototype_noise_0.0-optimizer.algo_Lean+LearnerInEM+PseudoLabel+UpdateEnd
Showing first 10 runs
0500m11.5cost-per-image0.40.450.50.550.60.65
11-02-20-bayes-linear_nn-learner.features_moco-learner.early_stop_val-n_prototype_data_per_class_5-prototype_noise_0.2-optimizer.algo_LearnerInEM+PseudoLabel+UpdateEnd
11-02-20-bayes-linear_nn-learner.features_moco-learner.early_stop_approx_all-n_prototype_data_per_class_5-prototype_noise_0.2-optimizer.algo_LearnerInEM+PseudoLabel+UpdateEnd
11-02-20-bayes-linear_nn-learner.features_moco-learner.early_stop_val-n_prototype_data_per_class_5-prototype_noise_0.2-optimizer.algo_Lean+LearnerInEM+PseudoLabel+UpdateEnd
11-02-20-bayes-linear_nn-learner.features_moco-learner.early_stop_approx_all-n_prototype_data_per_class_10-prototype_noise_0.0-optimizer.algo_LearnerInEM+PseudoLabel+UpdateEnd
11-02-20-bayes-linear_nn-learner.features_moco-learner.early_stop_approx_all-n_prototype_data_per_class_5-prototype_noise_0.0-optimizer.algo_LearnerInEM+PseudoLabel+UpdateEnd
11-02-20-bayes-linear_nn-learner.features_moco-learner.early_stop_approx_all-n_prototype_data_per_class_10-prototype_noise_0.2-optimizer.algo_Lean+LearnerInEM+PseudoLabel+UpdateEnd
11-02-20-bayes-linear_nn-learner.features_moco-learner.early_stop_approx_all-n_prototype_data_per_class_10-prototype_noise_0.2-optimizer.algo_LearnerInEM+PseudoLabel+UpdateEnd
11-02-20-bayes-linear_nn-learner.features_moco-learner.early_stop_approx_all-n_prototype_data_per_class_5-prototype_noise_0.2-optimizer.algo_Lean+LearnerInEM+PseudoLabel+UpdateEnd
11-02-20-bayes-linear_nn-learner.features_moco-learner.early_stop_approx_all-n_prototype_data_per_class_5-prototype_noise_0.0-optimizer.algo_Lean+LearnerInEM+PseudoLabel+UpdateEnd
11-02-20-bayes-linear_nn-learner.features_moco-learner.early_stop_val-n_prototype_data_per_class_10-prototype_noise_0.2-optimizer.algo_Lean+LearnerInEM+PseudoLabel+UpdateEnd
Showing first 10 runs
0500m11.5cost-per-image0.70.750.80.850.90.951
11-02-20-bayes-linear_nn-learner.features_moco-learner.early_stop_val-n_prototype_data_per_class_5-prototype_noise_0.2-optimizer.algo_LearnerInEM+PseudoLabel+UpdateEnd
11-02-20-bayes-linear_nn-learner.features_moco-learner.early_stop_approx_all-n_prototype_data_per_class_5-prototype_noise_0.2-optimizer.algo_LearnerInEM+PseudoLabel+UpdateEnd
11-02-20-bayes-linear_nn-learner.features_moco-learner.early_stop_val-n_prototype_data_per_class_5-prototype_noise_0.2-optimizer.algo_Lean+LearnerInEM+PseudoLabel+UpdateEnd
11-02-20-bayes-linear_nn-learner.features_moco-learner.early_stop_approx_all-n_prototype_data_per_class_10-prototype_noise_0.0-optimizer.algo_LearnerInEM+PseudoLabel+UpdateEnd
11-02-20-bayes-linear_nn-learner.features_moco-learner.early_stop_approx_all-n_prototype_data_per_class_5-prototype_noise_0.0-optimizer.algo_LearnerInEM+PseudoLabel+UpdateEnd
11-02-20-bayes-linear_nn-learner.features_moco-learner.early_stop_approx_all-n_prototype_data_per_class_10-prototype_noise_0.2-optimizer.algo_Lean+LearnerInEM+PseudoLabel+UpdateEnd
11-02-20-bayes-linear_nn-learner.features_moco-learner.early_stop_approx_all-n_prototype_data_per_class_10-prototype_noise_0.2-optimizer.algo_LearnerInEM+PseudoLabel+UpdateEnd
11-02-20-bayes-linear_nn-learner.features_moco-learner.early_stop_approx_all-n_prototype_data_per_class_5-prototype_noise_0.2-optimizer.algo_Lean+LearnerInEM+PseudoLabel+UpdateEnd
11-02-20-bayes-linear_nn-learner.features_moco-learner.early_stop_approx_all-n_prototype_data_per_class_5-prototype_noise_0.0-optimizer.algo_Lean+LearnerInEM+PseudoLabel+UpdateEnd
11-02-20-bayes-linear_nn-learner.features_moco-learner.early_stop_val-n_prototype_data_per_class_10-prototype_noise_0.2-optimizer.algo_Lean+LearnerInEM+PseudoLabel+UpdateEnd
BYOL
64
Simclr
64
Moco
64
Simclr+Moco
64


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https://wandb.ai/andrewliao11/knn_crowdsourcing/reports/Different-features--VmlldzozMDMwODE
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