Questions tagged [pretraining]

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What is the common practice for NLP or text mining for non-English?

A lot of natural language processing tools are pre-trained with corpus in English. What if ones need to analyze, say, Dutch text? The blogs I find online are mostly saying traslating text into English ...
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1answer
26 views

Where to get models with weights instead of only weights? What's the purpose of .h5 files?

I have downloaded .h5 files from qubvel/resnet and qubvel/efficientnet. I was trying to use some models as a backbone for my model but I'm getting the following ...
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51 views

Would there be any reason to pretrain BERT on specific texts?

So the official BERT English model is trained on Wikipedia and BookCurpos (source). Now, for example, let's say I want to use BERT for Movies tag recommendation. Is there any reason for me to pretrain ...
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10 views

(Pre)training an Embedding Layer via prediction (as an alternative to similarity) - does that makes sense?

Similarity is the go-to way to train embeddings - use a similarity matrix (eg dot product) between the embeddings of two inputs, train to increase it for connected inputs and decrease it for inputs ...
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1answer
60 views

How to access GPT-3, BERT or alike?

I am interested in accessing NLP models mentioned in scientific papers, to replicate some results and experiment. But I only see waiting lists https://openai.com/blog/openai-api/ and licenses granted ...
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24 views

Pretrained CNN model on animal dataset ( turtles images if exist )

I was wondering if there is a pretrained CNN model on an animal dataset. I am participating in a turtle face detection competition and was wondering if there was a pretrained image model to fine tune ...
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2answers
30 views

Logic behind pre-trained weights and transfer learning

I am not sure about the logic behind, how pre-trained weights actually make sense and translate into a new problem. To be more specific; for example in a object detection network, how would a model's ...
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15 views

With one pretrained CNN model do I get only one vector of descriptors for an image?

I am given a dataset of 2D medical images. I am asked to extract image descriptors from the hidden layer of the neural network pre-trained on the ImageNet dataset. I consider to use two networks: ...
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2answers
178 views

Does finetuning BERT involving updating all of the parameters or just the final classification layer?

Currently learning and reading about transformer models, I get that during the pretraining stage the BERT model is trained on a large corpus via MLM and NSP. But during finetuning, for example trying ...
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33 views

Any pretrained models for Style Transfer trained with large images (>512px)?

I have found some pretrained models that are prepared for small image sizes. https://tfhub.dev/google/magenta/arbitrary-image-stylization-v1-256/2' (256x256px) https://keras.io/api/applications/vgg/#...
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1answer
670 views

Deploying multiple pre-trained model (tar.gz files) on Sagemaker in a single endpoint

We have followed the following steps: Trained 5 TensorFlow models in local machine using 5 different training sets. Saved those in .h5 format. Converted those into tar.gz (Model1.tar.gz,...Model5.tar....
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13 views

How to use an encoder to do feature extraction

I'm newbie with all of data science. I have a pre-trained U-Net network from which I get its encoder. Now I have to use a picture to get its features. With the whole U-Net I do this with fit method: <...
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1answer
35 views

Are there any objections to using the same (unlabelled) data for pre-training of a BERT-Based model and the downstream task?

I'm looking to train an Electra model using unlabelled data in a specific field. Are there any objections to using the same data for unsupervised learning and then using the same data downstream for ...
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146 views

How to go about fine-tuning BERT using a next-sentence task

I've got a large corpus of documents, and I want to use bert to generate embeddings for a variety of predictive tasks. The documents are multi-sentence, in a non-standard domain, and have labels at ...
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1answer
62 views

Semantic segmentation with greyscale images

I'm trying to reproduce a research with greyscale images instead of colour images. I have found that there are pre-trained networks, like VGG16, with ImageNet. But that dataset has colour images, and ...
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1answer
16 views

Question of pretraining text-generation task, it seems that pretraining is not work for a small model?

My task is to generate keywords from sentences. I pretrain a text-generation model. I mask the sentences' tokens and predict the whole sentences' tokens. Pretraining batch_size = 8 and step = 1000000 ...