Questions tagged [training]

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

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18 views

What kind of problems cannot be solved using machine learning techniques?

For the problems that can be solved algorithmically. We have very good formal literature for which problems can be solved in polynomial, exponential time and which cannot. P/NP/NP-hard But do we ...
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1answer
22 views

What does it mean to train a model?

We hear this many time for different problems Train a model to solve this problem! What do we really mean by training a model?
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1answer
13 views

How do LSTM or GRU gates learn to specialize in their desired tasks?

While I was studying the equations for the computation inside GRU and LSTM units, I realized that although the different gates have different Weight matrices, their overall structure is the same. They ...
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15 views

How can I build a model that replaces a feature of one image with another feature?

I would like to build a neural network (using TensorFlow) that is able to take two animals, and replace a feature in the second with one in the first. For example, if given a dog and cat, the cat's ...
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1answer
36 views

Is there a way of deriving a loss function given the neural network and training data?

There is some sort of art to using the right loss function. However, I was wondering if there is a way to derive the loss function if I gave you a neural network model (the weights) as well as the ...
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1answer
28 views

Why do we also need to normalize the action's values on continuous action spaces?

I was reading here tips & tricks for training in DRL and I noticed the following: always normalize your observation space when you can, i.e., when you know the boundaries normalize your ...
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14 views

Low accuracy during training for text summarization

I am trying to implement an extractive text summarization model. I am using keras and tensorflow. I have used bert sentence embeddings and the embeddings are fed into an LSTM layer and then to a Dense ...
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9 views

Training a model for text document transformation?

I have a bunch of text documents, split into source documents and transformed documents. These text documents have multiple lines and are edited at specific locations, in a specific way. I make use ...
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0answers
13 views

How to save and load a Q-Learning Agent [migrated]

I know this may sound nooby, but how do I save a Deep Q-Learning agent's progress? I mean when I close at i.e. episode 500 when my agent is trained and I restart (in my case a pygame) my agent is ...
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0answers
26 views

Confidence Interval around prediction with bootstrapping

I want to generate a confidence interval around my prediction (vector) $\hat{y}$. I have implemented the following procedure. However, I am not sure whether this makes sense in a statistical way: I ...
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1answer
31 views

Is the test time the phase when the model's accuracy is calculated with test data set?

When papers talk about the "test time", does this mean the phase when the model is passed with new data instances to derive the accuracy of the test data set? Or is "test time" the phase when the ...
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0answers
8 views

How to train-test split and cross-validate in surprise? [migrated]

I wrote the following code below which works: ...
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3answers
116 views

What is the difference between training and testing in reinforcement learning?

In reinforcement learning (RL), what is the difference between training and testing an algorithm/agent? If I understood correctly, testing is also referred to as evaluation. As I see it, both imply ...
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1answer
27 views

Does Q Learning learn from an opponent playing random moves?

I've created a Q Learning algorithm to play Connect Four against an opponent who just chooses a random free column. My Q Agent is currently only winning about 0.49 games on average (30,000 episodes). ...
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1answer
24 views

What is meant by the expected BLEU cost when training with BLEU and SIMILE?

Recently I was reading a paper based on a new evaluation metric SIMILE. In a section, validation loss comparison had been made for SIMILE and BLEU. The plot showed the expected BLEU cost when training ...
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1answer
22 views

Should I just use exploitation after I have trained the Q agent?

When using a trained Q-learning algorithm in an actual game, would I just use exploitation and no longer use exploration? Should I use exploration only during the training phase?
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31 views

Are there any papers on this alternate neural net training approach?

I developed a custom callback for Keras. Initially, it monitors training accuracy. If on a given epoch the accuracy is below that of the previous epoch it lowers the learning rate by a factor. If for ...
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0answers
30 views

Convolutional Neural Network Training on Different Datasets

I currently want to train a CNN but I have two small datasets that are slightly different because of the camera setup that captured the images. I'm interested in ultimately tuning the neural network ...
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0answers
23 views

Can neural networks handle redundant inputs?

I have a fully connected neural network with the following number of neurons in each layer [4, 20, 20, 20, ..., 1]. I am using TensorFlow and the 4 real-valued ...
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0answers
18 views

Why does this tutorial on reinforced learning not check whether the environment is 'game over' during training?

I am following the tutorial Train a Deep Q Network with TF-Agents. It uses the hello world environment of reinforced learning: cart pole. At the end, the agent is ...
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3answers
84 views

How to improve neural network training against a large data set of points with varying magnitude

I am currently using TensorFlow and have simply been trying to train a neural network directly against a large continuous data set, e.g. $y = [0.014, 1.545, 10.232, 0.948, ...]$ corresponding to ...
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0answers
24 views

How to make binary neural networks resilient to flipped activation values?

Assume I am given a binary neural network where the activation values are constrained to be 0 or 1 (by clipping the ReLU function). Additionally, assume the neural network is supposed to work in a ...
1
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1answer
59 views

If the i.i.d. assumption holds, shouldn't the training and validation trends be exactly the same?

If the i.i.d. (independent and identically distributed) assumption holds for a training-validation set pair, shouldn't their loss trends be exactly the same, since every batch from the validation set ...
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2answers
37 views

What does it mean if classification error is equal between two networks but the MSE is different?

I'm experimenting with training a feedforward neural network using a genetic algorithm and I've done a few tests using both the mean squared error and classification error functions as fitness ...
2
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1answer
43 views

After having selected the best model with cross-validation, for how long should I train it?

When using k-fold cross-validation in a deep learning problem, after you have computed your hyper-parameters, how do you decide how long to train your final model? My understanding is that, after the ...
1
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1answer
27 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 ...
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1answer
49 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
46 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
18 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
25 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
14 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
27 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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2answers
288 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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2answers
48 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 ...
2
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1answer
22 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
843 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
34 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
14 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
81 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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2answers
45 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
13 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
36 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
29 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
9 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
21 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
25 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 ...
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1answer
39 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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