Kartik sachdevkartik

## augmentation.py
from typing import Optional
from torchvision import transforms
from PIL import Image
import albumentations as A
from albumentations.pytorch import ToTensorV2
from torch.utils.data import DataLoader, Dataset


def get_transform_train(
    upsample_size: int, final_size: int, channels: Optional[int] = 1

## hyperparameters.csv

          
            Hyperparameter
             Value

            
              Batch size
               64

            
              Epochs
               15

            
              Image channels
               1

            
              Optimizer
               AdamW

            
              Weight decay
               0.01

            
              Learning rate schedule
               Cosine schedule with warmup

            
              Initial learning rate
               0.01

## twinssvt_config.py
TWINSSVT_CONFIG = {
    "network_type": "TwinsSVT",
    "pretrained": False,
    "image_size": 224,
    "batch_size": 64,
    "num_epochs": 15,
    "optimizer_config": {
        "name": "AdamW",
        "weight_decay": 0.01,
        "lr": 0.001,

## validation_accuracy.csv

          
            Architecture
             Model_I
             Model_II
             Model_III

            
              Convolutional Vision Transformer
               91.54%
               99.41%
               99.04%

            
              CrossFormer
               91.20%
               97.42%
               98.13%

            
              LeViT
               91.64%
               97.12%
               97.97%

            
              TwinsSVT
               91.08%
               97.44%
               98.48%

            
              CCT
               89.71%
               69.68%
               99.48%

            
              CrossViT
               84.20%
               91.33%
               81.29%

            
              CaiT
               67.93%
               62.97%
               69.38%

            
              T2TViT
               88.12%
               94.33%
               77.29%

            
              PiT
               40.63%
               33.60%
               34.18%
	from typing import Optional
	from torchvision import transforms
	from PIL import Image
	import albumentations as A
	from albumentations.pytorch import ToTensorV2
	from torch.utils.data import DataLoader, Dataset


	def get_transform_train(
	upsample_size: int, final_size: int, channels: Optional[int] = 1
	Hyperparameter	Value
	Batch size	64
	Epochs	15
	Image channels	1
	Optimizer	AdamW
	Weight decay	0.01
	Learning rate schedule	Cosine schedule with warmup
	Initial learning rate	0.01
	TWINSSVT_CONFIG = {
	"network_type": "TwinsSVT",
	"pretrained": False,
	"image_size": 224,
	"batch_size": 64,
	"num_epochs": 15,
	"optimizer_config": {
	"name": "AdamW",
	"weight_decay": 0.01,
	"lr": 0.001,
Architecture	Model_I	Model_II	Model_III
Convolutional Vision Transformer	91.54%	99.41%	99.04%
CrossFormer	91.20%	97.42%	98.13%
LeViT	91.64%	97.12%	97.97%
TwinsSVT	91.08%	97.44%	98.48%
CCT	89.71%	69.68%	99.48%
CrossViT	84.20%	91.33%	81.29%
CaiT	67.93%	62.97%	69.38%
T2TViT	88.12%	94.33%	77.29%
PiT	40.63%	33.60%	34.18%