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View Code? Open in Web Editor NEWPytorch code for "Improving Self-Supervised Learning by Characterizing Idealized Representations"
License: MIT License
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When will the paper about this project be released?
Many thanks for your insightful work. When will the paper about this project be released?
Reproducing the results on transfer tasks
Thanks a lot for your brilliant work. I'm trying to use your ImageNet pre-trained model dissl_resnet50_dNone_e400_m6 to train a linear probing and evaluate it on CIFAR-10. I followed the instructions in F.2. Featurized the data, and min-max scaled it into [0, 1]. Then use both logistic regression and SVC with parameter C to train it. The best result of both on the test set is about 83%. I attached the accuracies I got below.
| reg | LR_train | LR_test | SVC_train | SVC_test |
|---|---|---|---|---|
| -4.00 | 64.32 | 63.63 | 74.23 | 73.45 |
| -3.33 | 70.58 | 70.11 | 80.16 | 79.14 |
| -2.67 | 77.30 | 76.03 | 84.56 | 82.42 |
| -2.00 | 82.62 | 80.84 | 87.75 | 83.66 |
| -1.33 | 86.76 | 83.23 | 89.80 | 83.73 |
| -0.67 | 90.16 | 83.96 | 91.08 | 82.81 |
| 0.00 | 92.81 | 83.19 | 91.63 | 81.75 |
| 0.67 | 94.62 | 81.62 | 91.85 | 80.76 |
| 1.33 | 95.70 | 79.57 | 89.64 | 78.35 |
| 2.00 | 96.36 | 78.04 | 86.53 | 76.69 |
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