Questions tagged [training]

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

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Understanding graphs of the mean square error: relationships between val loss and train loss

I am currently working with some models aimed at predicting time series (89 days for training, 22 for testing), including a CNN LSTM and a convLSTM. When training these models, I had the following ...
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25 views

What would happen if validation set was the same as the training set?

Just to check if everything is working properly in my neural net, I set my validation data to be the same as my training data, expecting to achieve a better NRMS for validation data (since it uses ...
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1answer
30 views

How to input dataset with multi-value properties?

I'm trying to learn to use AI, and so I've followed some basic tutorials like training an MLP to predict the price of a car given properties like its age and manufacturer. Now I want to see if I can ...
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1answer
40 views

How to handle images that don’t pertain to image classifier at all?

I am trying to create a CNN model that classifies if a person is wearing a seatbelt or not to verify they drive safely. I know to get images of people wearing seatbelts and people not wearing ...
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1answer
49 views

How to predict the “word” based on the meaning in a document?

What I mean to say is For example, if I give the meaning of Apple from the dictionary as input to the program, it should give output as Apple. Or I say My day to day job involves monitoring and ...
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59 views

Is there a way to reduce the RMSE error when training a neural network to recognise MNIST digits using ANFIS?

I wanted to build a digit recognition neural network using MATLAB ANFIS kit. I started by using the MNIST database and I figured out it's almost impossible to classify 784 dimension data using ANFIS. ...
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53 views

How large should the corpus be to optimally retrain the GPT-2 model?

I just started working with the GPT-2 models and want to retrain one on a pretty narrow topic, so I have problems finding training material. How large should the corpus be to optimally retrain the GPT-...
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40 views

How can I build a deep reinforcement learning model that can be trained with multiple time series datasets

I built a DRL model to trade stocks in the financial market but the number of observations is relatively small and I would like to increase it by training the same model with stocks from several ...
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1answer
52 views

How are training hyperparameters determined for large models?

When training relatively small DL model which takes several hours to train, I typically start with some starting points from literature and then use trial-and-error or grid-search approach to tune up ...
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2answers
69 views

How can I predict the true label for data with incomplete features based on the trained model with data with more features?

Suppose I have a model that was trained with a dataset that contains the features (f1, f2, f3, f4, f5, f6). However, my test dataset does not contain all features ...
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75 views

Forcing a neural network to be close to a previous model - Regularization through given model

I'm wondering, has anyone seen any paper where one trains a network but biases it to produce similar outputs to a given model (such as one given from expert opinion or it being a previously trained ...
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1answer
80 views

Why can't we train neural networks in a peer-to-peer manner?

I have recently been exposed to the concept of decentralized applications, I know that neural networks require a lot of parallel computing infra for training. What are the technical difficulties one ...
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1answer
64 views

What is the purpose of a Neural Network in Reinforcement Learning when we have a Q-learning update rule?

I'm confused as to the purpose of training a neural network (NN) for reinforcement learning (RL) tasks such as Gridworld. In RL tasks, namely q-learning, we have a q-learning update rule, which is ...
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36 views

What is the amount of test data needed to evaluate a CNN?

I have an image dataset of about 400 images. 70% of these data points were used for training, 15% for validation, and 15% for testing. I am using the 70% to train a CNN-based binary classifier. I ...
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39 views

Why is it that having a duplicate in features set makes training to work bad

I'm defining a deep network to emulate a multitarget regression. When I costruct my training set, I take information from a graph; without going into too much detail, it could happen that I take 2 ...
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58 views

Finding the 'ultimate resolution' of an ANN

I want to use a neural network to predict the refractive index of a solution. My thinking is, instead of immediately training on many samples, I will first find the 'ultimate resolution' of the ...
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33 views

Isn't it true that using max over a softmax will be much slower because there is not a smooth gradient?

Isn't it true that using max over a softmax will be much slower because there is not a smooth gradient? Max basically zeros out the gradients of all the non-maximum values. Especially at the beginning ...
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30 views

Is it necessary to label the background when generating the labelled dataset for semantic segmentation?

When I label images for semantic segmentation (using u-net, if that matters), is labeling the background (anything I am not interested in) necessary? Will it improve the network's performance?
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1answer
42 views

How should we interpret all the different metrics in reinforcement learning?

I'm trying to train some deep RL agents using policy gradient methods like AC and PPO. While training, I have a ton of different metrics being monitored. I understand that the ultimate goal is to ...
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34 views

Where can I find a training text for some specific intents in English?

Where can I find a training text for some specific intents in English? For example, the intent of asking for an appointment, or asking for contact info exchange? Is there any recommended source of ...
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1answer
28 views

How to manually collect rectangular training data samples from images?

I want to collect training samples from images. That can mean different things depending on the context. I think of the simplest case, which should be most commonly required. Because it is so common, ...
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0answers
19 views

Algorithm to train a neural network against differentiable and non-differentiable databases?

Let's say I have two databases, $(\mathbf{x_i}, \mathbf{\hat{p_i}})$ and $(\mathbf{x_j}, \mathbf{\hat{q_j}})$. A neural network with weights $\theta$ can receive an input $\mathbf{x}$ and produce an ...
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1answer
43 views

Intuitively, why can the training of a neural network be formulated as a probability estimation problem?

Neural network training problems are oftentimes formulated as probability estimation problems (such as autoregressive models). How does one intuitively understand this idea?
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2answers
44 views

How to combine several chatbots into one?

I'm in the middle of a project in which I want to generate a TV series script (characters answering to each other, scene by scene) using SOTA models, and I need some guidance to simplify my ...
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1answer
27 views

How to split data into training validation and test set when the number of data in classes varies greatly?

I have 5 classes of pictures to classify: 0 -> ~3 200 (~800 initial number before interference and duplication) 1 -> ~9 000 (I reduced from ~90 000) 2 -> ~8 000 3 -> ~3 000 4 -> ~7 200 How to ...
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37 views

What are the training and optimization technique to train GPT-2 with 1.5B parameters?

I am able to train 345M parameter GPT-2 using DialoGPT on Reddit data topics like AskReddit, Askmen, AskWomen, casualConvo, etc. And I using AWS p3dn.24xlarge instance with 256GB GPU. It is trained ...
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0answers
35 views

How many training runs are needed to obtain a credible value for performance?

I'm trying to optimize a neural network. For that, I'm changing parameters like the batch size, learning rate, weight initialization, etc. A neural network is not a deterministic algorithm, so, in ...
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2answers
61 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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2answers
50 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
33 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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28 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
46 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
62 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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24 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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0answers
20 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
34 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
42 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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3answers
150 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
39 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
32 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
33 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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39 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
38 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
37 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
25 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
96 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
31 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 ...
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1answer
69 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
45 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
51 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 ...

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