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Questions tagged [training]

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

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15 views

Finetuning GPT-2 twice for particular style of writing on a particular topic

Sorry if this is a stupid question. I'm just starting out in ML and am working with gpt-2 for text generation. My situation is that I have to generate text in a particular field for eg. family ...
3
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0answers
25 views

How to train a model to extract custom and unknown entities

I'm trying to figure out how to extract specific text from an utterance by a user. I need to extract "unknown" text from a short and simple text. In this case, the user wants to create a list. ...
7
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1answer
91 views

Will quantum computing have any kind of effect on the development of AI?

Recently, according to some reports Google achieved something called 'Quantum Supremacy'. Whether its true or not remains to be seen. But my question is does Quantum Computers or the principle they ...
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0answers
23 views

What is the state of the art AI training technique for imperfect information 2 player turn based games?

As far as I can tell (correct me if I'm wrong), Alphazero (with MCTS and neural network heuristic function RL) is the state of the art training method for turn based, deterministic, perfect ...
5
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1answer
38 views

Why do very deep non resnet architectures perform worse compared to shallower ones for the same iteration? Shouldn't they just train slower?

My understanding of the vanishing gradient problem in deep networks is that as backprop progresses through the layers the gradients become small, and thus training progresses slower. I'm having a hard ...
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7 views

Fusing label distribution and on-hot encoded labels

A while ago I came across a paper for image classification that utilized both label distribution and one-hot encoded labels to classify images. An image has a label distribution for all classes (4 ...
2
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0answers
30 views

How to transfer learn Darknet YOLOv3

I've started getting into object detection in image. I have YOLOv3 neural network with Darknet framework. The network is pre-trained from COCO data set. Now I need to do some transfer learning in ...
3
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1answer
34 views

GPU/TPU acceleration for neural networks with various network topologies

I was thinking about different neural network topologies for some applications. However, I am not sure how this would affect the efficiency of hardware acceleration using GPU/TPU/some other chip. If, ...
5
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1answer
77 views

Why evolutionary training of neural networks is not popular?

Evolutionary algorithms are mentioned in some sources as possible to be used to train a neural network (finding weights, not hyperparameters), however I have not heard about one practical application ...
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0answers
18 views

A2C for the game of Hanabi underfits

I am trying to solve the game of Hanabi (paper describing game) with actor-critic algorithm. I took code for the environment from the Deepmind's repository and implemented a2c algorithm myself. From ...
3
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1answer
31 views

Reinforcement learning with hints or reference model

In Reinforcement Learning, when I train a model, it comes up with its own set of solutions. For example, if I am training a robot to walk, it will come up with its own walking gait, such as this Deep ...
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0answers
14 views

Invalid moves in Deep Reinforcement Learning for games [duplicate]

I've been working on a bot for a game involving dice throws and chance. The architecture involved is similar to AlphaZero in the that it has Convolutions and MCTS. According to the current state ...
2
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1answer
22 views

Will a .h5 file trained with Xception model work with Resnet50?

I have been running my 2013 server box since 2 weeks ago for training an AI model. I set up 30 epochs to run but since than it only ran 1 epoch as my PC config is super slow. But it generates 1 .h5 ...
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3answers
89 views

Accuracy too high too fast?

I have a simple text classifier, with the following structure: ...
2
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0answers
37 views

When to use RMSE as opposed to MSE and vice versa?

I understand that RMSE is just the square root of MSE. Generally, as far as I have seen, people seem to use MSE as a loss function and RMSE for evaluation purposes, since it exactly gives you the ...
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0answers
13 views

Training, validation loss and accuracy yolov3?

This is a version of Yolo V3 implemented in PyTorch – YOLOv3 in PyTorch I am trying to use transfer learning to train this yolov3 implementation following the directions given in this post. This is ...
2
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2answers
99 views

What are the reasons a perceptron is not able to learn?

I'm just starting to learn about neural networking and I decided to study a simple 3-input perceptron to get started with. I am also only using binary inputs to gain a full understanding of how the ...
0
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1answer
49 views

Why do I get a straight line as an output from a neural network?

I am using feedforward neural network for regression and what I get as a result of prediction is a constant value visible on the graph below: Data I use are typical standardised tabular numbers. The ...
5
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3answers
54 views

What should we do when we have equal observations with different labels?

Suppose we have a labeled data set with columns $A$, $B$, and $C$ and a binary outcome variable $X$. Suppose we have rows as follows: ...
3
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4answers
186 views

What could an oscillating training loss curve represent?

I tried to create a simple model that receives an $80 \times 130$ pixel image. I only had 35 images and 10 test images. I trained this model for a binary classification task. The architecture of the ...
1
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1answer
19 views

Train on big dataset (1mil + images)

I am in the process of collecting a huge dataset of Human poses captured images to create a model to classify poses. My question is how will I be able to train on this massive dataset? I have ...
4
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2answers
842 views

What is the “thing” which is trained in AI model training

I am a newbie in the fantastic AI world, I have started my learning recently. After a while, my understanding is, we need to feed in tremendous data to train a or many models. Once the training is ...
2
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1answer
47 views

What does it mean for AlphaZero's network to be “fully trained”

Reading this blog post about AlphaZero: https://deepmind.com/blog/article/alphazero-shedding-new-light-grand-games-chess-shogi-and-go It uses language such as "the amount of training the network ...
4
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2answers
319 views

Iteratively and adaptively increasing the network size during training

For an experiment that I'm working on, I want to train a deep network in a special way. I want to initialize and train a small network first, then, in a specific way, I want to increase network depth ...
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0answers
10 views

A NN based model of a Cattle for 'Heat Detection'

I am very new to AI/ML but have lot of interest in these. I am trying to understand how this gadget works. So far I have understood that a NN model of the cattle is generated by offline ...
0
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0answers
33 views

Not able to properly tune Neural Network via Back Propagation properly

I have a custom code Neural Network(not using keras or any package...Trying to learn the essence of Neural Network from scratch)... Code can be found here I have the per iteration training output(<...
1
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0answers
19 views

Train detector : 300 images with 30 objects or 9000 images with one?

so I have this dataset of images of people sitting in a restaurant. I've annotated about 300 images with an average of 30 instances of "person" per image. Now I'm wondering if I should have annotated ...
1
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1answer
21 views

Model Performance and Size of Data Set

Suppose we have a data set with $4,000$ labeled examples. The outcome variable is trinary (three possible categorical values). Suppose the accuracy of a given model is "bad" (e.g. less than $50 \%$). ...
1
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0answers
24 views

AI for Warcraft 3 Dota

I want to create AI for Dota1. Is it possible to create AI for Warcraft 3? How Open AI works in Dota2? I want to know more about algorithms what are in foundation in Open AI.
1
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0answers
18 views

i have trained my model & now trying to predict but unable to do using keras

i have trained my model & now trying to predict but unable to do please help. trying to predict cat or dog stuck in "prediction" ...
2
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1answer
36 views

How is a neural network where the majority of inputs are 0 trained?

Take alexnet. Alexnet has 1000 output nodes, each of which classify an image: The problem I have been having with training a neural network of similar proportions, is that it does what any reasonable ...
0
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0answers
17 views

Is a Q&A web application content good to be used to train a closed domain chat-bot?

Background I am currently trying to implement Stack Overflow for Teams where I work and this should cover Q & As about various topics from administrative / HR to internal programming questions. ...
2
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0answers
61 views

How can I incrementally train a Yolo model without catastrophic forgetting?

I have successfully trained a Yolo model to recognize k classes. Now I want to train by adding k+1 class to the pre-trained weights (k classes) without forgetting previous k classes. Ideally, I want ...
0
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0answers
32 views

What to look for when CNN returns same prediction for every input?

I am trying to use a CNN to do a regression prediction on some statistical data. The data is time-series data formatted into a 2-D grid. The network I'm using looks like this: ...
1
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0answers
12 views

Binary annotations on large, heterogenous images

I'm working on a deep learning project and have encountered a problem. The images that I'm using are very large and extremely detailed. They also contain a huge amount of necessary visual information, ...
2
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1answer
40 views

Decreasing Loss, Constant Accuracy

Problem Statement I've built a classifier to classify a dataset consisting of n samples and four classes of data. To this end, I've used pretrained VGG-19, pretrained Alexnet and even lenet (with ...
0
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1answer
28 views

Ideal score of a model on training and cross validation data

The question is little bit broad, but I could not find any concrete explanation anywhere, hence decided to ask the experts here. I have trained a classifier model for binary classification task. Now ...
2
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1answer
43 views

Leave One Out Testing

I am currently working with a small dataset of 20x300. Since I have so few datapoints, I was wondering if I could use an approach similar to leave-one-out cross-validation but for testing. Here's ...
0
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0answers
36 views

Can't create datasets and load images in COCO annotator

I'm trying to annotate images with COCO key points for pose estimation using https://github.com/jsbroks/coco-annotator. As described in the Installation section I cloned the repo. I installed Docker ...
1
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2answers
66 views

Divide classes into truncated and non-truncated objects

At the moment I am working on a vehicle counting & classification project. For a specific part in the project I need to get back only the completely visible vehicles from my input data (images). ...
1
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2answers
77 views

Drone training, how to train without training data?

I setupped a small drone simulator using PhysX, the time step is at 200 hz, while motors update like regular ESCs (at 50 Hz). I computed the inertia matrix, tweaked a bit mass of components to be real,...
2
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0answers
38 views

Difference between retraining on different portions of data and training initially on larger data set

I have a large data set that doesn't fit in memory and would have to use something like Keras's model.fit_generator if I would like to train the model on all of the ...
2
votes
1answer
28 views

Adding input features - is complete re-training required?

I've never worked with very large models that require weeks or months of training, but in such a situation, what happens if you want to add extra features inputs, do you need to re-train the entire ...
4
votes
2answers
161 views

Use Machine Learning/Artificial Intelligence to predict next number (n+1) in a given sequence of random increasing integers

The AI must predict the next number in a given sequence of incremental integers (with no obvious pattern) using Python but so far I don't get the intended result! I tried changing the learning rate ...
0
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0answers
18 views

Benefits in using multiple LSTM layers?

I am working on a time series forecasting problem and I am in the process of choosing the optimum network structure. Currently I have a 200 cell LSTM layer fully connected to 100 neurons in an ...
2
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1answer
20 views

Is it mostly the case to train with available models

I quite often find projects using pre-trained model and using them as a starting point for their new model that learns something novel from thier dataset or on-live learning process - e.g. using a ...
2
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1answer
30 views

how to benefit from previous training weights in training again to increase accuracy?

I have trained a modified VGG classification CNN, with random initialized weights; therefor the validation accuracy was not high enough for me to accept (around 66%). now using the weights resulted ...
3
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1answer
120 views

Why are not validation accuracy and loss as smooth as train accuracy and loss?

I am training a modified VGG16 network for classification (adding 0.5 dropout after each of the last FC layers). In the following plot I am training for a small number of epochs as an example, and it ...
0
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1answer
33 views

CNN output generally has more than one category in one-hot categorization?

I'm a bit of a CNN newbie, and I'm trying to train one to image classify pictures of pretty similar looking particles. I'm making the inputs and labels by hand from a set of 48x48 grayscale images, ...
2
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1answer
64 views

Can I calculate the training performance of GPUs by comparing their specification?

I am currently using Nvidia GTX1050 with 640 CUDA cores and 2GB GDDR5 for Deep Neural Network training. I want to buy a new GPU for training, but I am not sure how much performance improvement I can ...