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update README

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@@ -11,9 +11,9 @@ license: mit
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  Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
 
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- ## For Assignment 13
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-
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  First I took Rohan shared input file, S13.ipy that is an S11 reference, where resnet code exists with lots of gradio examples.
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  Ensured it builds successfully.
@@ -33,3 +33,53 @@ I integrated above said three items such as gradcam for multiple images, misclas
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  Fourthly I started working on above working code to modularize it so that few py files will hold major part of code.
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  I started working on HuggingFace and created / updated required files and it is made to be in working state in HuggingFace.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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+ ## Assignment 13
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+ ### What is done and how
 
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  First I took Rohan shared input file, S13.ipy that is an S11 reference, where resnet code exists with lots of gradio examples.
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  Ensured it builds successfully.
 
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  Fourthly I started working on above working code to modularize it so that few py files will hold major part of code.
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  I started working on HuggingFace and created / updated required files and it is made to be in working state in HuggingFace.
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+ My spaces app has these features:
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+ 1. Asks the user whether he/she wants to see GradCAM images and how many, and from which layer, allow opacity change as well
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+ 2. Asks whether he/she wants to view misclassified images, and how many
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+ 3. Allow users to upload new images, as well as provide 10 example images
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+ In a tabbed interface, gradio framework is used and available for use from HuggingFace.
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+ HuggingFace https://huggingface.co/spaces/raja5259/eraV2s13_raj
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+ Github https://github.com/rajayourfriend/EraV2/
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+
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+ ### Log of Training
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+ Below is the log of training with pytorch lightning for 26 epochs with 6.6M params and got a test_acc of 91.28%
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+ INFO:pytorch_lightning.utilities.rank_zero:GPU available: True (cuda), used: True
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+ INFO:pytorch_lightning.utilities.rank_zero:TPU available: False, using: 0 TPU cores
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+ INFO:pytorch_lightning.utilities.rank_zero:IPU available: False, using: 0 IPUs
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+ INFO:pytorch_lightning.utilities.rank_zero:HPU available: False, using: 0 HPUs
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+ Files already downloaded and verified
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+ Files already downloaded and verified
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+ INFO:pytorch_lightning.accelerators.cuda:LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]
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+ INFO:pytorch_lightning.callbacks.model_summary:
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+ | Name | Type | Params
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+ ----------------------------------
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+ 0 | model | Net_S13 | 6.6 M
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+ ----------------------------------
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+ 6.6 M Trainable params
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+ 0 Non-trainable params
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+ 6.6 M Total params
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+ 26.293 Total estimated model params size (MB)
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+ Epoch 25: 100%
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+  197/197 [00:23<00:00,  8.53it/s, loss=0.0844, v_num=3, val_loss=0.261, val_acc=0.916]
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+ INFO:pytorch_lightning.utilities.rank_zero:`Trainer.fit` stopped: `max_epochs=26` reached.
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+ Files already downloaded and verified
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+ Files already downloaded and verified
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+ INFO:pytorch_lightning.accelerators.cuda:LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]
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+ Testing DataLoader 0: 100%
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+  40/40 [00:03<00:00, 11.30it/s]
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+ ┏━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
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+ ┃ Test metric ┃ DataLoader 0 ┃
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+ ┑━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━┩
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+ β”‚ test_acc β”‚ 0.9128999710083008 β”‚
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+ β”‚ test_loss β”‚ 0.2818313539028168 β”‚
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+ β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”΄β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜
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+ [{'test_loss': 0.2818313539028168, 'test_acc': 0.9128999710083008}]
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