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How to add multiple embeddings (layers) to LSTM layer

Let's consider the main approaches: Embed each categorical feature, then LSTM on top. I think you want to opt for individual recurrent layers when the features are sort of mutually exclusive, i.e. ...
Luca Anzalone's user avatar
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more insights about Word2Vec implementation

Bag of words(BOW) is a term generally used for the assumption where one doesn"t care about the order of the words. Words are usually treated as a ...
lateBloomer's user avatar
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Appropriate input size for nn.Embedding

nn.embedding layer is a sytactic sugar equivalent to one hot vector+ linear layer. Suppose you have 2 distinct variables. and you want your model to learn their ...
lateBloomer's user avatar
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Dealing with varying predictive horizon

My understanding of your sample data is that you have X1, X2 as predictors, and two things you want to predict: whether target will be 0 or 1, and how many months before that result happens. So, one ...
Darren Cook's user avatar
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What is the relationship between the accuracy and the loss in deep learning?

Ayúdenme a aclarar esta duda por favor Después de ver este comentario: ------si sus datos están entre 0 y 1, una pérdida de 0,5 es enorme, pero si sus datos están entre 0 y 255, un error de 0,5 es ...
jhazmin tapia's user avatar
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What Deep Learning model to use in this spectroscopy task?

I think you need a deep learning model that can perform both image segmentation and image classification. Image segmentation is the process of dividing an image into regions or pixels that share some ...
Halis Yılboğa's user avatar
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Why does cost function on a neural network increase?

I had similar problems and for me the reason was that my regularization parameter lambda was too high. I removed regularization completely and set it to 0 (that would be a good starting point). I was ...
Flavius Miron's user avatar
1 vote

Build a topic model without data?

Yes, you certainly can, but understand that this would be a first step to getting your model off the ground and then later on you can refine the predictions and retrain the model to make it better. ...
Jesse Sealand's user avatar
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Prediction interval around LSTM time series forecast

You can easily quantify uncertainty for time series models using conformal prediction Here is an article about doing it with classical models ...
valeman's user avatar
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3 votes

Why my validation loss and accuracy decays over epochs?

You are experiencing a lot of overfitting on the training set here. I would go back and see if there are any inherent issues with the data (scaling? class imbalance? etc.) before diving into modeling. ...
NLP from scratch's user avatar
0 votes

LMM Fine Tuning - Supervised Fine Tuning Trainer (SFTTrainer) vs transformers Trainer

The short answer is that a Supervised Fine Tuning Trainer (SFTTrainer) is used for Instruct Fine Tuning. The HuggingFace library SFTTrainer has also support for training with QLoRA (4-bit Quantised ...
Alex Punnen's user avatar

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