I’m training my model on around 4000 Chest X-Ray images using Transfer Learning (EfficientNet B1). The training is as follows: Epoch 1/10 99/99 [==============================] – 1437s 14s/step – loss: 0.6446 – accuracy: 0.8617 – val_loss: 0.3128 – val_accuracy: 0.9178 Epoch 2/10 99/99 [==============================] – 193s 2s/step – loss: 0.2179 – accuracy: 0.9356 – val_loss: 0.4521 ..
How to modified the number of neurons of the last fully-connected layer as 2 for binary classification in Keras? Source: Python..
I am training an image classification model on sagemaker with input data configurations as: Train test split is 70-30 15 classes with data sizes in test ranging from 40-3000. For train, the class sample sizes range from 100-7000. Model configurations for training in sagemaker are: num_layers = 18 image_shape = "3,700,800" num_classes = class_count mini_batch_size ..
I am working on NLP using a distilbert pretrained model that I’m finetuning. I’m using Keras Adam optimiser. Root mean square error is my loss function. I am splitting the data into a few folds and running each fold several epochs. The following are my loss curves each fold. I am a beginner and need ..
I’m implementing PyTorch’s transfer learning tutorial to classify images to three classes. I want to enhance/improve the tutorial’s code to plot the training and validation losses overtime but not sure how to do it. The tutorial code is here https://pytorch.org/tutorials/beginner/transfer_learning_tutorial.html I think, somewhere in this code block, I need to plot the graph. def train_model(model, ..
We are currently working on an image classification task for detecting tuberculosis from chest x-ray images. You can see our code below. We used 0.7 for the train set, 0.2 for the validation set, and 0.1 for the test set. Our training and validation loss is here . But when we try it on our ..
In the Lesson 8 video tutorial, Jeremy said we can use the pretrained Wiki model to train our own model. And I do remember that he said something about after the transfer learning the language model of your own will not only have the corpus from the pre-trained Wiki model, but also the vocabulary from ..
ValueError: Graph disconnected: cannot obtain value for tensor Tensor("input_1:0", shape=(None, 288, 288, 3), dtype=float32) at layer "stem_conv". The following previous layers were accessed without issue:  I’m using github/qubvel efficientnet and segmentation_networks implementations, and trying to connect the last bilinear upsize layer to efficientnet via a conv2d layer. but I get the above error. Here ..
I’m currently working on an iOS App where I want to detect if there is a table, chair or bench in the current camera input. My idea was to take the MobileNetV2 model and get it to classify these three categories with transfer learning in TensorFlow. Because there are cases where none of these three ..
I want to use pre-trained AlexNet to classify non-classified images in my dataset and I get a RuntimeError: stack expects each tensor to be equal size, but got [3, 224, 224] at entry 0 and [4, 224, 224] at entry 19 in 417 cell of my Jupyter Notebook. Could you, please, help me with such ..