Final simclr (#170)

* cleared docs * cleared docs * cleared docs
Lightning-Universe · Aug 23, 2020 · cf38307 · cf38307
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diff --git a/docs/source/self_supervised_models.rst b/docs/source/self_supervised_models.rst
@@ -165,19 +165,19 @@ CIFAR-10 baseline
      - Hardware
      - LR
    * - `Original <https://github.com/google-research/simclr#finetuning-the-linear-head-linear-eval>`_
-     - `82.00? <https://github.com/google-research/simclr#finetuning-the-linear-head-linear-eval>`_
-     - resnet (depth 18)
+     - `92.00? <https://github.com/google-research/simclr#finetuning-the-linear-head-linear-eval>`_
+     - resnet50
      - LARS
      - 512
      - 1000
      - 1 V100 (32GB)
      - 1.0
    * - Ours
-     - `86.75 <https://tensorboard.dev/experiment/mh3qnIdaQcWA9d4XkErNEA>`_
+     - `85.68 <https://tensorboard.dev/experiment/GlS1eLXMQsqh3T5DAec6UQ/#scalars>`_
      - `resnet50 <https://github.com/PyTorchLightning/PyTorch-Lightning-Bolts/blob/master/pl_bolts/models/self_supervised/resnets.py#L301-L309>`_
      - `LARS <https://pytorch-lightning-bolts.readthedocs.io/en/latest/api/pl_bolts.optimizers.lars_scheduling.html#pl_bolts.optimizers.lars_scheduling.LARSWrapper>`_
      - 512
-     - 698 (10 hr)
+     - 960 (12 hr)
      - 1 V100 (32GB)
      - 1e-6
 
@@ -187,7 +187,7 @@ CIFAR-10 pretrained model::
 
     from pl_bolts.models.self_supervised import SimCLR
 
-    weight_path = 'https://pl-bolts-weights.s3.us-east-2.amazonaws.com/simclr/simclr-cifar10-v1-exp2_acc_867/epoch%3D698.ckpt'
+    weight_path = 'https://pl-bolts-weights.s3.us-east-2.amazonaws.com/simclr/simclr-cifar10-v1-exp12_87_52/epoch%3D960.ckpt'
     simclr = SimCLR.load_from_checkpoint(weight_path, strict=False)
 
     simclr.freeze()

diff --git a/pl_bolts/models/self_supervised/simclr/simclr_finetuner.py b/pl_bolts/models/self_supervised/simclr/simclr_finetuner.py
@@ -44,7 +44,7 @@ def cli_main():  # pragma: no-cover
         dm.val_transforms = SimCLREvalDataTransform(h)
 
     # finetune
-    tuner = SSLFineTuner(backbone, in_features=2048 * 2 * 2, num_classes=dm.num_classes)
+    tuner = SSLFineTuner(backbone, in_features=2048 * 2 * 2, num_classes=dm.num_classes, hidden_dim=None)
     trainer = pl.Trainer.from_argparse_args(args, early_stop_callback=True)
     trainer.fit(tuner, dm)