I tried to implement the lesson 1 is it a bird or forest. I am getting error rate as 1 for epochs. But when i use it the model predicts the bird or forest correctly. This is my first time doing anything in DL so i dont know what to make out of this.
PFA the snapshot of my jupyter runtime
can you try another model than resnet18 and see what result you will get?
Tried with resnet34, same display. I also tried to plot confusion matrix. I am guessing that it might have something to do with error rate but there was no confusion as per the plot.
I have installed fastai, pytorch using miniconda, I dont know may be the distribution here is not proper.
Will give it a try using mamba as suggested in the course or colab
the models are overfitting to your dataset which is small by the way, try to have a bigger dataset try for example hundreds of bird images and hundreds of forest images
I am having this issue as well. I am getting an error_rate of 1.0000
I tried to change the model to look for butterfly and mountain (instead of bird or forest) respectively, and i when training, I still get an error rate of 1.0000
It correctly predicts a butterfly with probability of 1.0000
however, interestingly, when i pass in the original bird.jpg, it also predicts that it is a butterfly with a probability of 0.9739
for reference, here is my ss:
interestingly, this is what I got in colab when i executed the datablock. Bottom left is not a butterfly…