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@ -72,7 +72,7 @@ Feature evaluation is done using a linear model protocol.
Features are learned using the ```STL10 train+unsupervised``` set and evaluated in the ```test``` set;
Check the [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/sthalles/SimCLR/blob/9d071bb3dd93e921217c415cf0924aad2d0b13eb/feature_eval/linear_feature_eval.ipynb) notebook for reproducebility.
Check the [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/sthalles/SimCLR/blob/9d071bb3dd93e921217c415cf0924aad2d0b13eb/feature_eval/linear_feature_eval.ipynb) notebook for reproducibility.
| Linear Classifier | Feature Extractor | Architecture | Feature dimension | Project Head dimension | Trained for (# epochs) | STL10 Top 1 |
|:-------------------:|:-----------------:|:------------:|:-----------------:|:-----------------------:|:----------------------:|:-----------:|