RachitKumar

Getting very less accuracy for Image

1

``` class` FashionMNIStModelV0(nn.Module): def __init__(self,input_features,hidden_units,output_features): super().__init__() self.layer_stack=nn.Sequential( nn.Flatten(), nn.Linear(in_features=input_features,out_features=hidden_units), nn.Linear(in_features=hidden_units,out_features=output_features) ) def forward(self,x): return self.layer_stack(x) model_0=FashionMNIStModelV0(input_features=784,hidden_units=10,output_features=len(class_names)).to("cpu") My Training Model ''' from tqdm.auto import tqdm torch.manual_seed(42) train_time_start_on_cpu = timer() #set the...

Different inputs on Conv2d

3

What is the input we need to provide for the model Conv2d (Tiny VGG) . When i send the image in shape [1,28,28] it fails , but when i unsqueeze(dim=0)...

Evaluation of Model

3

Hi All , Wanted to understand , when we evaluate using the plot_decision_boundary. But how do we test the model apart from it. Do we give the new test values...