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title: EraV2s13 Raj | |
emoji: π | |
colorFrom: gray | |
colorTo: purple | |
sdk: gradio | |
sdk_version: 4.28.3 | |
app_file: app.py | |
pinned: false | |
license: mit | |
Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference | |
## Assignment 13 | |
### What is done and how | |
First I took Rohan shared input file, S13.ipy that is an S11 reference, where resnet code exists with lots of gradio examples. | |
Ensured it builds successfully. | |
Then I replaced the model to my model of S11. | |
Prepared the code in such a way that on a condition check, the training and save of weights would happen in one path. Otherwise loading the weights, it would perform testing. This weight file is .pth. | |
Secondly I took Rohan shared input file, cifar10-baseline.ipynb that is an S13 reference, where pytorch lightning code of a working model is present. | |
Ensured it builds successfully. | |
Then I replaced the model to my model of S11. | |
Prepared the code in such a way that on a condition check, the training and save of weights would happen in one path. Otherwise loading the weights, it would perform testing. This weight file is .ckpt. | |
Thirdly I started working on the gradio with gradcam and made it working for a single image input. | |
I started working on the gradio with misclassified image display and made it working. | |
I started working on the gradio with gradcam and made it working for a multiple images taken from cifar 10 misclassified images. | |
I started working on the gradio with 10 images inputter and made it working. Here it can accept 1 images and display them. Does not do anything further. | |
I integrated above said three items such as gradcam for multiple images, misclassified images, 10 images input in gradio. It works successfully. | |
Fourthly I started working on above working code to modularize it so that few py files will hold major part of code. | |
I started working on HuggingFace and created / updated required files and it is made to be in working state in HuggingFace. | |
My spaces app has these features: | |
1. Asks the user whether he/she wants to see GradCAM images and how many, and from which layer, allow opacity change as well | |
2. Asks whether he/she wants to view misclassified images, and how many | |
3. Allow users to upload new images, as well as provide 10 example images | |
In a tabbed interface, gradio framework is used and available for use from HuggingFace. | |
HuggingFace https://huggingface.co/spaces/raja5259/eraV2s13_raj | |
Github https://github.com/rajayourfriend/EraV2/ | |
### Log of Training | |
Below is the log of training with pytorch lightning for 26 epochs with 6.6M params and got a test_acc of 91.28% | |
INFO:pytorch_lightning.utilities.rank_zero:GPU available: True (cuda), used: True | |
INFO:pytorch_lightning.utilities.rank_zero:TPU available: False, using: 0 TPU cores | |
INFO:pytorch_lightning.utilities.rank_zero:IPU available: False, using: 0 IPUs | |
INFO:pytorch_lightning.utilities.rank_zero:HPU available: False, using: 0 HPUs | |
Files already downloaded and verified | |
Files already downloaded and verified | |
INFO:pytorch_lightning.accelerators.cuda:LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0] | |
INFO:pytorch_lightning.callbacks.model_summary: | |
| Name | Type | Params | |
---------------------------------- | |
0 | model | Net_S13 | 6.6 M | |
---------------------------------- | |
6.6 M Trainable params | |
0 Non-trainable params | |
6.6 M Total params | |
26.293 Total estimated model params size (MB) | |
Epochβ25:β100% | |
β197/197β[00:23<00:00,ββ8.53it/s,βloss=0.0844,βv_num=3,βval_loss=0.261,βval_acc=0.916] | |
INFO:pytorch_lightning.utilities.rank_zero:`Trainer.fit` stopped: `max_epochs=26` reached. | |
Files already downloaded and verified | |
Files already downloaded and verified | |
INFO:pytorch_lightning.accelerators.cuda:LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0] | |
TestingβDataLoaderβ0:β100% | |
β40/40β[00:03<00:00,β11.30it/s] | |
βββββββββββββββββββββββββββββ³ββββββββββββββββββββββββββββ | |
β Test metric β DataLoader 0 β | |
β‘ββββββββββββββββββββββββββββββββββββββββββββββββββββββββ© | |
β test_acc β 0.9128999710083008 β | |
β test_loss β 0.2818313539028168 β | |
βββββββββββββββββββββββββββββ΄ββββββββββββββββββββββββββββ | |
[{'test_loss': 0.2818313539028168, 'test_acc': 0.9128999710083008}] | |