Questions tagged [training]

For questions about training networks, rules systems, or other AI system components.

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1answer
18 views

Should I be balancing the data before creating the vocab-to-index dictionary?

My question is about when to balance training data for sentiment analysis. Upon evaluating my training dataset, which has 3 labels (good, bad, neutral), I noticed there were twice as many neutral ...
2
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1answer
27 views

Stochastic gradient descent does not behave as expected, even with different activation functions

I have been working on my own AI for a while now, trying to implemented SGD with momentum from scratch in python. After looking around and studying all the maths behind it, i finally managed to ...
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2answers
38 views

Should I always start from the same start state in reinforcement learning?

In an episodic training of an RL agent, should I always start from the same initial state or I can start from several valid initial states? For example, in a gym environment, should my ...
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0answers
13 views

How can I implement a Facial Recognition algorithm in C++ from scratch, without using OpenCV?

I wanna implement an algorithm for Facial Recognition in C++ with the help of Viola-Jones, aka Adaboost, but without using OpenCV or any other similar library. I wanna do it all from scratch. Any tips?...
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2answers
23 views

What does it mean to have epochs=30 in Keras' fit method given certain data?

I have read a lot of information about several notions, like batch_size, epochs, iterations, but because of explanation was without numerical examples and I am not native speaker, I have some kind of ...
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0answers
13 views

How do weights changes handles during back-propagation when there are unknown labels

I have a question about how weights are updated during back-propagation for some of my samples that have unknown labels (please note, unknown, not missing). The reason they are unknown is because this ...
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0answers
22 views

What could cause a big fluctuation of the loss in the last epochs of training an AlexNet?

I am training an AlexNet neural network, with about 12000 images which 80% is for training, 10% is for validation and another 10% is for testing. I have a problem in my plots. There is a big ...
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1answer
24 views

Is it better to rely on an intention file or a database for a web chatbot?

Currently, I'm making a chatbot that is going to be functioning in a website, so I was wondering, is it better to train the chatbot with intentions files or use the database as the intention file, if ...
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1answer
102 views

Is my GRU model under-fitting given this plot of the training and validation loss?

I was running my gated recurrent unit (GRU) model. I wanted to get an opinion if my loss and validation loss graph is good or not, since I'm new to this and don't really know if that is considered ...
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0answers
16 views

can't reproduce model.fit with GradientTape [migrated]

I've been trying to investigate into the reason (e.g. by checking weights, gradients and activations during training) why SGD with a 0.001 learning rate worked in training while Adam fails to do so. (...
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2answers
43 views

What happens if I train a network for more epochs, without using early stopping?

I have a question about training a neural network for more epochs even after the network has converged without using early stopping criterion. Consider the MNIST dataset and a LeNet 300-100-10 dense ...
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1answer
17 views

Data scan not making sense for coco dataset

I am doing a simple scan to see how dataset size affects training. Basically, I took 10% of the coco dataset and trained a yolov3 net (from scratch) to just look for people. Then I took 20% of the ...
4
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1answer
833 views

What is the purpose of the batch size in neural networks?

Why is a batch size needed to update the weights of a neural network? According to that Youtube Video from 3B1B, the weights are updated by calculating the error between expectation and outcome of ...
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2answers
24 views

What are the reasons behind slow YOLO training?

I'm testing out YOLOv3 using the 'darknet' binary, and custom config. It trains rather slow. My testing out is only with 1 image, 1 class, and using YOLOv3-tiny instead of YOLOv3 full, but the ...
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0answers
13 views

AI Logistic center simulation [closed]

First of all, I am pretty new to python and Ai and never realised a project before. I am a PLC-programmer with experience, but never did anything like this: I was thinking about a logistic center ...
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2answers
52 views

Is this model overfitted or not?

I am training a neural network and plot model accuracy and model loss. I am a little confused about overfitting. Is my model overfitted or not? how can I interpret it EDIT: here is a sample of my ...
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1answer
67 views

Why is my loss (binary cross entropy) converging on ~0.6? (Task: Natural Language Inference)

I’m trying to debug my neural network (BERT fine-tuning) trained for natural language inference with binary classification of either entailment or contradiction. I've trained it for 80 epochs and its ...
2
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1answer
22 views

deep learning with kfold cross validation with epochs

I am new into neural networks, I want to use K-fold cross-validation to train my neural network. I want to use 5 folds 50 epochs and a batch size of 64 I found a function in scikit for k-fold cross ...
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1answer
30 views

Difference between training accuracy and calculating accuracy with class prediction

I have trained my neural network with a dataset of 11200 images, and its validation accuracy was 96%. I saved my model and load its weights to the same neural network. I chose 738 images of my dataset ...
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0answers
12 views

Why is the loss of one of the outputs of a model with multiple outputs increasing while the others are decreasing?

I'm a newbie in neural networks. I'm trying to fit my neural network that has 3 different outputs: semantic segmentation, box mask and box coordinates. When my model is training, the loss of ...
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0answers
33 views

Can AI be trained to create social media post?

I am trying to conduct an experiment for fun to see if AI could be trained to create "good" social media post. I pulled examples of 1,000s "good" social media post from Facebook. Can someone point ...
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0answers
25 views

How to reduce fluctuation of a neural network?

I've modeled an AlexNet neural network, with 50 epochs and a batch size of 64. I used a stochastic gradient descent optimizer with a learning rate of 0.01. I attached the train and validation loss and ...
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0answers
8 views

Multi user DL trainings: VMs VS Multi-seat configuration

For a project of Deep Learning for Detection algorithm (for e.g., improving YOLO) implying 4 users using the same hardware, is it more efficient to set the environment as each user has his own session ...
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0answers
19 views

Steps to train and re-train a good model

I'm still a bit new to deep learning. What I'm still struggling, is what is the best practice in re-training a good model over time? I've trained a deep model for my binary classification problem (...
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0answers
20 views

What is the use of concatenate layer in CNN?

I am not asking what does concatenate layer does in general in point of mathematical operation. But at feature level, what significance does it provide. Does it helps removing false negatives or does ...
1
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1answer
33 views

How does batch size affect model size?

I'm suffering from a significant brain fart while trying to get my head around how does batch size affect overall model size e.g for CNNs. Does it serve as an additional dimension for all the weight ...
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1answer
25 views

Choosing Data Augmentation smartly for different application

I'm trying to understand the role of data augmentation and how it can affect the performance/accuracy of a deep model. My target application is fire detection (on video frames), with almost 15K ...
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3answers
49 views

While we split data in training and test data, why we have two pairs of each?

Why do we split the data into two parts, and then split those segments into training and testing data? Why do we have two sets of data for each training and test data?
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2answers
44 views

Training accuracy vs validation accuracy on deep models

I'm training a deep network in Keras on some images for a binary classification (I have around 12K images). Once in a while, I collect some false positives and add ...
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0answers
20 views

Detect human names using positive dataset only?

As Named-Entity Recognition algorithm is a subtask of information extraction that seeks to locate and classify atomic elements in text into predefined categories such as the names of persons, ...
2
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2answers
57 views

How can I train a RL agent to play board games successfully without human play?

How would you go about training an RL Tic Tac Toe (well, any board game, really) application to learn how to play successfully (win the game), without a human having to play against the RL? ...
2
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0answers
16 views

What effect does increasing the actions in RL have?

Consider a 2D snake game, where the snake has to eat food to become longer. It must avoid hitting walls and biting into her tail. Such a game could have a different amount of actions: 3 actions: go ...
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1answer
84 views

How many layers exists in my neural network?

I have a neural network model defined as below. How many layers exist there? Not sure which ones to count when we are asked about the number. ...
2
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1answer
42 views

What are evolutionary algorithms for topology and weights evolving of ANN (TWEANN) other than NEAT?

I wonder, if there are other than NEAT approaches to evolving architectures and weights of artificial neural networks? To be more specific: I am looking for projects/frameworks/libraries that use ...
2
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1answer
35 views

When training a CNN, what are the hyperparameters to tune first?

I am training a convolutional neural network for object detection. Apart from the learning rate, what are the other hyperparameters that I should tune? And in what order of importance? Besides, I read ...
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0answers
18 views

Training dataset for convolutional neural network classification - will images captured on the ground be useful for training aerial imagery?

I am an agronomy graduate student looking to classify crops from weeds using convolutional neural networks (CNNs). The basic idea that I am wanting to get into involves separating crops from weeds ...
2
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3answers
38 views

How to deal with random weights initialization in hyperparameters tuning?

In the step of tuning my neural networks I often encounter a problem that every time I train the exact same network, it gives me different final error due to random initialization of the weights. ...
1
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1answer
47 views

Why does my model overfit on pseudo-random numbers training data?

I am trying to predict pseudo-random numbers using the past numbers with a multiplayer perceptron. The error while training is very low. However, as soon as I test it with a test set, the model ...
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0answers
20 views

Deduce properties of the loss functions from the training loss curves

I have two convex, smooth loss functions to minimise. During the training (a very simple model) using batch SGD (with tuned optimal learning rate for each loss function), I observe that the (log) loss ...
2
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0answers
14 views

Which CNN hyper-parameters are most sensitive to centered versus off centered data?

Which hyper-parameters of a convolutional neural network are likely to be the most sensitive to depending on whether the training (and test and inference) data involves only accurately centered images ...
2
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1answer
51 views

How difficult is this sound classification?

I want a microphone to pick up sounds around me (let's say beyond a 3 foot radius), but ignore sounds made at my desk, such as the rustling of paper, clicking a mouse and typing, my hands brushing up ...
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1answer
44 views

not sure if fine-tuned network is finely-tuned

I am practicing with Resnet50 fine tuning for binary classification task, here is my code snippet. ...
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0answers
20 views

Is there any app / API which generates meaningful information?

I was wondering if there is any application / API which given a word comes up with legible and meaningful information related to it, and if possible relates it to any recent happenings or development ...
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1answer
32 views

How to explain peak in training history of a convolutional neural network?

I am training a simple convolutional neural network to recognize two types of 1024-point frequency spectra (FFT). This is the model I'm using: ...
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2answers
24 views

Automated Annotation of Objects

Given thousands of images, where some of the images contain target objects and others do not, is there an easy way of drawing bounding boxes on these target objects rather than relying on manual ...
4
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0answers
49 views

Training and inference for highly-context-sensitive information

What is the best way to train / do inference when the context matters highly as to what the inferred result should be? For example in the image below all people are standing upright, but because of ...
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0answers
35 views

How can I build a model to approximate the function $f(n) = 2n$?

I made the following HTML nd javascript to predict $f(n) = 2n$. Basically, I am trying to design my first neural network which predicts 2 multiplied by a number. I know we don't need a neural network ...
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0answers
28 views

Relationship between model complexity (depth) and dataset size

I'm new to deep learning. I was wondering what's the relationship between a deep model complexity (e.g. total number of parameters, or depth) and the dataset size? Assuming I want to do a binary ...
2
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1answer
36 views

What would be the implications of mistakenly adding bias after the activation function?

I was looking at the source code for a personal project neural network implementation, and the bias for each node was mistakenly applied after the activation function. The output of each node was ...
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0answers
45 views

Reinforcement learning for a 2D game involving two players

I'd like to create an AI for a 2D game involving two players fighting against each other. The map look something like this (The map is a NxN array somehow randomly generated): Basically the players ...

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