I want to train a model that perform a few-shot image classification using CIFAR-10. So I have to train the model with a small amount of classes and use the rest of the classes for the testing. I'm wondering if I have only 10 classes, how can i do the split? (For example 6 classes for training and 4 for testing, is it ok?)
How to split classes in few-shot classification using CIFAR-10?
311 Views Asked by Giulia At
1
There are 1 best solutions below
Related Questions in PYTORCH
- Pytorch install with anaconda error
- How should I save the model of PyTorch if I want it loadable by OpenCV dnn module
- PyTorch: memorize output from several layers of sequencial
- in Pytorch, restore the model parameters but the same initial loss
- Seq2seq pytorch Inference slow
- Why does autograd not produce gradient for intermediate variables?
- pytorch inception model outputs the wrong label for every input image
- "expected CPU tensor(got CUDA tensor)" error for PyTorch
- Float16 (HalfTensor) in pytorch + cuda
- Access parameter names in torch
- Efficient way of calculating sum of unequal sized chunks of tensor in Pytorch
- what is the equivalent of theano.tensor.clip in pytorch?
- How can I do scatter and gather operations in NumPy?
- How do I write a PyTorch sequential model?
- How to combine multiple models together?
Related Questions in ARTIFICIAL-INTELLIGENCE
- Developing a Checkers (Draughts) engine, how to begin?
- STRIPS representation of monkey in the lab
- Difference between weak AI and strong AI?
- Q-learning in game not working as expected
- How do I use a class as a template in C#?
- prolog rules as arguments
- How to evaluate a recurrent connection in an artificial neural network?
- AS3 AI barrier detection and movement
- How to simulate neural network by changing different parameters after training in MATLAB?
- Debugging Neural Network for (Natural Language) Tagging
- How do I create a back propagation neural network that has different kinds of output?
- Google Deep Dream art: how to pick a layer in a neural network and enhance it
- Pylearn2 example for time series or sequence prediction
- A Star Pathfinding
- Using Neural Networks Without Training Them
Related Questions in META-LEARNING
- How to implement Meta learning on the base model(neural network)
- Incompatible shapes:[512] vs. [512,1024]
- GradientTape.gradient() returns `None` type
- Is this the process of meta-learning MAML for inner loop and outer loop training?
- Too much fluctuation in F1 Score curve during meta training with MAML
- Why is RandomCrop with size 84 and padding 8 returning an image size of 84 and not 100 in pytorch?
- How to combine multiple dataset efficiently to solve using meta learning?
- How to use the trained model in meta learning
- Is this the correct implementation of a MAML model?
- Failing to compute gradient in PyTorch
- How to split classes in few-shot classification using CIFAR-10?
- Meta-learning to find optimal model from pre-trained models in Tensorflow
- When training with MAML and Siamese networks, I've encountered issues where the weights aren't updating or the accuracy remains unchanged
- Vanishing parameters in MAML JAX (Meta Learning)
- How does one create a distributed data loader with PyTorch's TorchMeta for meta-learning?
Related Questions in FEW-SHOT-LEARNING
- How to format a few-shot prompt for GPT4 Chat Completion API?
- How to re-use embedded documents for Few-Shot LLM queries in Langchain4j?
- Too much fluctuation in F1 Score curve during meta training with MAML
- How to combine multiple dataset efficiently to solve using meta learning?
- What are the differences between adapter tuning and prefix tuning?
- Encountering zero division error while trying run this code, the nsamples read zero values
- AttributeError: module 'os' has no attribute 'killpg'
- Can I use only one query image per class in Few-shot Learning?
- How to split classes in few-shot classification using CIFAR-10?
- setfit training with a pandas dataframe
- What are the differences between fine tuning and few shot learning?
- Explanation for the Few-shot learning paradigm in Computer vision classification
- sql_agent returning parser error in Ajax llm
- Using locally saved SetFit model
- convert few shot learning example to API
Trending Questions
- UIImageView Frame Doesn't Reflect Constraints
- Is it possible to use adb commands to click on a view by finding its ID?
- How to create a new web character symbol recognizable by html/javascript?
- Why isn't my CSS3 animation smooth in Google Chrome (but very smooth on other browsers)?
- Heap Gives Page Fault
- Connect ffmpeg to Visual Studio 2008
- Both Object- and ValueAnimator jumps when Duration is set above API LvL 24
- How to avoid default initialization of objects in std::vector?
- second argument of the command line arguments in a format other than char** argv or char* argv[]
- How to improve efficiency of algorithm which generates next lexicographic permutation?
- Navigating to the another actvity app getting crash in android
- How to read the particular message format in android and store in sqlite database?
- Resetting inventory status after order is cancelled
- Efficiently compute powers of X in SSE/AVX
- Insert into an external database using ajax and php : POST 500 (Internal Server Error)
Popular Questions
- How do I undo the most recent local commits in Git?
- How can I remove a specific item from an array in JavaScript?
- How do I delete a Git branch locally and remotely?
- Find all files containing a specific text (string) on Linux?
- How do I revert a Git repository to a previous commit?
- How do I create an HTML button that acts like a link?
- How do I check out a remote Git branch?
- How do I force "git pull" to overwrite local files?
- How do I list all files of a directory?
- How to check whether a string contains a substring in JavaScript?
- How do I redirect to another webpage?
- How can I iterate over rows in a Pandas DataFrame?
- How do I convert a String to an int in Java?
- Does Python have a string 'contains' substring method?
- How do I check if a string contains a specific word?
I have not completely understand your question. We have three options to say it crudely:
If it is the number 3 is what you are looking for, I would recommend that you look into models like CLIP and see whether they work out for your use case.