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@ -26,7 +26,7 @@ $ python run.py -data ./datasets --dataset-name stl10 --log-every-n-steps 100 --
If you want to run it on CPU (for debugging purposes) use the ```--disable-cuda``` option.
For 16-bit precision GPU training, make sure to install [!NVIDIA apex](https://github.com/NVIDIA/apex) and used the ```--fp16_precision``` flag.
For 16-bit precision GPU training, make sure to install [NVIDIA apex](https://github.com/NVIDIA/apex) and use the ```--fp16_precision``` flag.
## Feature Evaluation
@ -41,4 +41,4 @@ Check the [![Open In Colab](https://colab.research.google.com/assets/colab-badge
|----------------------------|---------|-------------------|---------------------------------------------------------------------------------|------------------------|--------------------------------|--------|--------|
| Logistic Regression (Adam) | STL10 | SimCLR | [ResNet-18](https://drive.google.com/open?id=14_nH2FkyKbt61cieQDiSbBVNP8-gtwgF) | 512 | 128 | 100 | 70.45 |
| Logistic Regression (Adam) | CIFAR10 | SimCLR | [ResNet-18](https://drive.google.com/open?id=1lc2aoVtrAetGn0PnTkOyFzPCIucOJq7C) | 512 | 128 | 100 | 64.82 |
| Logistic Regression (Adam) | STL10 | SimCLR | [ResNet-50](https://drive.google.com/open?id=1ByTKAUsdm_X7tLcii6oAEl5qFRqRMZSu) | 2048 | 128 | 50 | 67.075 |
| Logistic Regression (Adam) | STL10 | SimCLR | [ResNet-50](https://drive.google.com/open?id=1ByTKAUsdm_X7tLcii6oAEl5qFRqRMZSu) | 2048 | 128 | 50 | 67.075 |