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Questions tagged [training-datasets]

For questions related to the dataset used to train machine learning models, such as neural networks. The training dataset is different from the validation and test datasets, which are used for early stopping (and/or hyperparameter optimization) and to test the final model's performance, respectively.

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How does Training and Validating work with Graph CNNs

I'm training a Graph Convolutional Neural Network to output embeddings for nodes that I eventually want to perform classification on. I am a little confused on how the training, validation, and ...
Kiran Manicka's user avatar
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10 views

Predict outputs based on a variable subset of inputs

To simplify this: I have 5 columns in my dataset -> A, B, C, D and E. I want the neural network to predict the rest of the outputs based on a subset of inputs. For example: Case #1 Inputs -> (A) ...
Sam's user avatar
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38 views

Does DPO update the weights in the same way that LORA/Fine-Tuining does?

I've been working on making a conversational customer service fine-tune for the past couple months and now I am looking to improve its failure recovery. For example, If the agent makes a mistake, how ...
the-test-set-is-all-you-need's user avatar
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0 answers
23 views

Chat with your DB: How to get AI to follow your rules?

Context/Background: I have a single table in MySQL with info on 'members', including things like location, favourite types of music, favourite camping spots, etc. Required Behaviour: I need the system ...
Blue Da Noob's user avatar
2 votes
1 answer
212 views

Human trainers: collect data by 2-alternative force choice (2AFC)

To collect human intelligence data, we intend to use 2-alternative force choice (2AFC). A sample human intelligence task (HIT) is shown below. Can it be considered a 2AFC? Is such a HIT considered ...
Megidd's user avatar
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2 answers
54 views

Can too much trainingdata have a negative impact?

I have to detect objects in an image. I want to use a neural network for this (yolov8). Since my objects are stacked, most of them are partially hidden and only front and side is visible. My dataset ...
Ef Ge's user avatar
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1 vote
0 answers
52 views

Largest fully open source LLMs including training

It seems that most of the open-sourced large language models (LLMs) like Llama 2 had the model released but not the exact training procedure and training data-sources (exact data revisions) so that ...
Kozuch's user avatar
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1 answer
109 views

XML Input to assist in composing muusic

First time submitter here. I'm a composer of (for want of a better term) contemporary classical music - and I would like to use AI to improve my productivity. The specific issue I'm dealing with is ...
E Heilner's user avatar
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0 answers
20 views

Same prediction result with little probabilities change

I built a job prediction system leveraging data scrapped from LinkedIn with Random Forest and compared it to XGBoost. XGBoost was used due to its high accuracy after training. When I made a prediction,...
ezaryf's user avatar
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2 votes
1 answer
344 views

Why are some LLMs trained on both CommonCrawl and Wikipedia/StackExchange?

Some LLMs are trained on both CommonCrawl and Wikipedia/StackExchange. Why? Does CommonCrawl already contain Wikipedia/StackExchange? E.g., from the LLaMa 1 paper: and from https://huggingface.co/...
Franck Dernoncourt's user avatar
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4 views

Individual Data point size within a dataset for finetuning for translation

I need to fine tuning a LLM for a translation task for specific domain. Could someone please advise if length of each data point within the data set has any impact on eventual performance of the LLMs. ...
user11740597's user avatar
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1 answer
42 views

How to label missing/default values for a named entity recognition dataset

I am building the training dataset for a named entity recognition model, with 2 tags: Name and Category and I am using a pre-...
mrang's user avatar
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1 vote
1 answer
370 views

What causes my loss curve to consistently oscillate when training an LLM?

Why is my loss curve consistently oscillating? Every 50 steps it jumps back up. I'm assumming there's a bug in my data, since I'm using this colab notebook that shows a proper train/loss at the bottom....
bmatzelle's user avatar
1 vote
0 answers
39 views

Is there a neural network architecture specialized for mapping lower-to-higher-dimensional data?

I am building a neural network that takes in a set of 86 parameters (primarily architecture-related, such as building floor area, kitchen size, number of a certain type of furniture, etc.) and outputs ...
JS4137's user avatar
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1 answer
56 views

Open access Adept-like dataset? (LLM-to-computer-input) [closed]

Here's a demo for Adept ACT-1 for Transformers. I don't doubt that one could create a demo video using zero-shot; actually I tested just now and the basic chat.openai.com interface was able to do some ...
llllvvuu's user avatar
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2 votes
1 answer
300 views

What's the architecture and size of neural-network-based reward models as used in reinforcement learning by human feedback

My rough understanding of RLHF as used for ChatGPT in a nutshell is this: A reward model is trained using comparisons of different responses to the same prompt. Human trainers rank these responses ...
Hans-Peter Stricker's user avatar
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0 answers
11 views

Can I combined the trained model between different source but same model structure?

Here I got two different deep-learning models that were trained by LSTM and time-series data. The data is the usage percentage of CPU from two different computers. Each computer job was the same. It ...
orde.r's user avatar
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2 votes
2 answers
81 views

Is there a measure of model complexity?

Is there a measure of model complexity?
Justaperson's user avatar
0 votes
1 answer
53 views

AI and Machine Learning Prediction Algorithms for predicting outcome results of Hypothetical poll

Can artificial intelligence and Machine Learning Prediction Algorithms assist in deciding the Outome Results of a Hypothetical Online Poll? Poll: Selecting favorite American President till date. ...
Prashant Akerkar's user avatar
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0 answers
110 views

Can AI be used for submarine detection?

Recently a lot of work has been done in connection to using AI in the search for extraterestrial life, the SETI project. Could the same methodology be used by the military, in order to detect ...
Cristian Dumitrescu's user avatar
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0 answers
25 views

Longer DNN training times when using evolutionary algorithms

I am comparing my deep neural network (DNN) performance when using 2 types of optimizers: gradient-based Adam (properly tuned) and a population-based optimization algorithm (e.g., genetic algorithm (...
knowledge_seeker's user avatar
1 vote
1 answer
83 views

Creating a Dataset from Time Series Data

Context I'd like to build a regression model for this data to predict a user's test scores given their study habits. Basically, the variables are in two separate csv tables similar to the ones below. ...
LittleLulatsch's user avatar
0 votes
1 answer
62 views

What papers can I read that explore model performance vs dataset size?

I am trying to estimate how many images I need to label for an object detection task. I understand a lot of variables are at play, but I'd like to find some papers that have already explored this ...
Alexis Winters's user avatar
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0 answers
295 views

When would you use prompting vs. fine tuning?

I would like to hear your thoughts on when is it appropriate to use prompting vs. fine-tuning. Does one make more sense for specific tasks than the other. Kindly elaborate.
Josiah Cheruiyot's user avatar
0 votes
2 answers
88 views

Why does linearly decreasing batch sizes result in exponentially increasing training times?

I'm quite new to machine learning and wanted to ask a question regarding why reducing batch sizes cause exponentially increasing training times. An example of this relationship between batch size and ...
Alpy's user avatar
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6 votes
1 answer
2k views

How was ChatGPT trained?

I know that large language models like GPT-3 are trained simply to continue pieces of text that have been scraped from the web. But how was ChatGPT trained, which, while also having a good ...
HelloGoodbye's user avatar
9 votes
1 answer
1k views

What causes ChatGPT to generate responses that refer to itself as a bot or LM?

ChatGPT occasionally generates responses to prompts that refer to itself as a "bot" or "language model." For instance, when given a certain input (the first paragraph of this ...
Obie 2.0's user avatar
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1 vote
0 answers
234 views

Is it possible to create an AI that produces output without giving it input?

AFAIK an AI is first trained using a data set of input and output values. After the training proccess you can give the AI input and it will produce output. For example when you write a sentence to an ...
zomega's user avatar
  • 119
1 vote
1 answer
3k views

Fine-tune GPT-Neo with prompt and completion?

I'm new to AI and machine learning. To fine-tune GPT-3, I understand that we need a set of training examples that each consist of a single input ("prompt") and its associated output ("...
SoftTimur's user avatar
  • 111
1 vote
0 answers
30 views

bad prediction when having noise on the data: LSTM time-series regression

I want to predict the force plate using a smart insole using the LSTM model for time series prediction. the data on the force plate has positive and negative values (I think the resulting positive ...
stack offer's user avatar
3 votes
4 answers
1k views

How is MNIST only providing the training and the test sets? What about the validation?

I was taught that, usually, a dataset has to be divided into three parts: Training set - for learning purposes Validation set - for picking the model which minimize the loss on this set Test test - ...
tail's user avatar
  • 157
1 vote
1 answer
350 views

Batching together similar length sequences to avoid padding and packing

I am training an RNN in PyTorch to produce captions for images. It's a pretty standard architecture – the image is processed by a pre-trained InceptionV3 to extract features, the recurrent module ...
czypsu's user avatar
  • 111
0 votes
1 answer
35 views

What kind of neural network and GPU should I use to classify images into > 10 000 classes?

I am trying to developp an image classifier that would have more than 10 000 classes but I don't know what kind of neural network I should use ? Some Other questions arise from this one : How big ...
Louis Delporte's user avatar
0 votes
0 answers
43 views

Is the neural network 100% accurate on training data if epoch loss is minimized to 0?

This seems like a silly, trivial question, but I just want to confirm it in case I'm missing something. I'm trying to train a ReLU neural network, which is supposed to be a function that satisfies ...
Acad's user avatar
  • 111
0 votes
1 answer
98 views

Storing training dataset in a platform like mlflow

I am pretty new to Machine learning and would like to know whether there are experiment management platforms that also allow storing and managing training datasets (images, in my case). I am familiar ...
Igor's user avatar
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1 vote
1 answer
97 views

Datasets input at model.fit produce unexpected results of training loss vs validation loss

Im trying to train a neural network (VAE) using tensorflow and Im getting different results based on the type of input in the model.fit. When I input arrays I get normal difference between the ...
user avatar
1 vote
0 answers
12 views

how to manage the impact of Covid on building a machine learning model

I need your suggestions for using historical data to build a machine learning model for analyzing the market and build an AI model(tree based model/random forest or regression analysis) for setting ...
Mahsa's user avatar
  • 111
1 vote
1 answer
170 views

Should I include overlapping (input) Data in my training data

If I have time dependent data and want to predict the relative change for a future time. Should I separate the data so that the input times don't overlap? With an example: I have hourly temperature ...
KarlTheGreat's user avatar
0 votes
0 answers
59 views

How to use oxford5k for training?

Generally, we have training data with landmark IDs, their GTs (positive samples), and then separate query images and corresponding positive samples for evaluation. In the Oxford5k or ROxford5k, one ...
David's user avatar
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1 vote
0 answers
72 views

Why does the SVM perform poorly on test data that has a different class distribution than the training data?

Do you know why the SVM performs poorly on test data that has a different class distribution than the training data? The training data has around 15 classes, and the additional testing data has around ...
Allie's user avatar
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0 votes
1 answer
52 views

How to create a dataset for binary classification

I would like to classify whether a pot of water is boiling or not using a CNN. Is it enough to take pictures of boiling water using only one pot, or should I use different pots for this to generalize ...
Joel Castro's user avatar
0 votes
1 answer
78 views

Is there a standard term for the following flaw in the data?

I wonder if following characteristic of data has some standard "professional" or scientific term associated with it. Let's assume that I have a set of dog/cat images labeled 0 for a cat and ...
GKozinski's user avatar
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0 votes
1 answer
78 views

Why "large set of training data" is needed in Neural Network AI training?

I often heard people saying, "large set of training data is needed for producing an accurate AI". But when I looked for articles explaining backpropagations online, it all seems like you ...
Noob002's user avatar
  • 11
2 votes
2 answers
494 views

How many unique angles of an object do you need in your image training set in order to correctly classify it?

I'm interested in using ResNet-50 to classify images of objects for around 1000 unique classes. I'm wondering if there is any way to estimate how many unique angles I need in my training set to ...
Tyler Hilbert's user avatar
5 votes
1 answer
747 views

How can I estimate how many photos I need to train ResNet-50 for image classification?

I am working on a project where I have to classify around 1000 unique objects. I'm trying to plan how much training data I will need to collect. I was planning on using ResNet-50. Is there anyway I ...
Tyler Hilbert's user avatar
0 votes
1 answer
68 views

Given a dataset of people with and without cancer, should I split it into training and test datasets such that the same person is not in both?

I have a database that contains healthy persons and lung cancer patients. I need to design a deep neural network for the binary classification problem (cancer/no cancer). I need to split the dataset ...
Noha's user avatar
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5 votes
2 answers
761 views

Do we need automatic hyper-parameter tuning when we have a large enough dataset?

Hyperparameter tuning is the process of selecting the optimal hyperparameters for an ANN. Now, my guess is that, if we have sufficient data (say, 1.4 million for, say, 6 features), the model can be ...
user366312's user avatar
1 vote
0 answers
36 views

Should I train a neural network with data with or without a constraint?

I want to train a Neural Network (NN) using a dataset. I want to use the NN model as a prediction function in one algorithm. However, in the algorithm, any data that does not meet a specific ...
Avishek Sinha Roy's user avatar
0 votes
1 answer
42 views

Does the ANN's training data include the proper output for every neuron?

I was designing an Artificial Neural Network a while back, but hit a bump when I got to the backpropagation. I was having trouble making the script choose whether to add or subtract from the weights, ...
Blue Herring's user avatar
2 votes
2 answers
74 views

Why not make the training set and validation set one if their roles are similar?

If the validation set is used to tune the hyperparameters and the training set adjusts the weights, why don't they be one thing as they have a similar role, as in improving the model?
Omar Zayed's user avatar