Fake-News-Classification
tf-transformers
Fake-News-Classification | tf-transformers | |
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1 | 5 | |
0 | 84 | |
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10.0 | 1.7 | |
about 2 years ago | about 1 year ago | |
Jupyter Notebook | Jupyter Notebook | |
- | Apache License 2.0 |
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Fake-News-Classification
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On Data Quality
For our capstone project at Flatiron school we had to not only pitch the project we wanted to do, but also find a dataset that would allow us to accomplish that project. I chose to make a Fake News Classifier, and pitched a dataset I found on Kaggle for it. My instructor was quick in turning it down. It had no information on how that data was acquired, how it was labelled, and I had no means of verifying it. With some more research done I found the Liar dataset, which contained thousands of data points, humanly labelled by editors from politifact.com using a truthiness scale and which contained extensive metadata on each instance, making it verifiable. Once I settled on my final model, I decided to train a version of it on the rejected dataset, just for curiosity. The Accuracy it provided for the test data from that dataset was way higher than the one trained in the Liar dataset. Why was that? The model wasn't actually making correct predictions, it was just better at identifying the labels (which were not verified) from the dataset.
tf-transformers
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Tensorflow-Transformers 2.0 ( for NLP, CV, Audio )
Code : GitHub - legacyai/tf-transformers: State of the art faster Natural Language Processing in Tensorflow 2.0 . 1 Website : https://legacyai.github.io/tf-transformers 1
- [P] Production Ready NLP Deep learning tutorials on tensorflow 2.0. tf-transformers
- Do we really need to Dstill Language Models? Joint loss is all we need - Albert-Joint .
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tf-transformers : State of the art faster NLP in Tensorflow 2.0 . 80 % faster to existing TF based libraries.
Faster Auto Regressive Decoding using Tensorflow2. Faster than PyTorch in most experiments (V100 GPU). 80% faster compared to existing TF based libraries (relative difference) Refer benchmark code.
- [D] Why is tensorflow so hated on and pytorch is the cool kids framework?
What are some alternatives?
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medspacy - Library for clinical NLP with spaCy.
liar_dataset - dataset liar
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MIRNet-TFJS - TensorFlow JS models for MIRNet for low-light💡 image enhancement
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BERT-for-Mobile - Compares the DistilBERT and MobileBERT architectures for mobile deployments.
gpt-3-simple-tutorial - Generate SQL from Natural Language Sentences using OpenAI's GPT-3 Model
transformers - 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
minGPT-TF - A minimal TF2 re-implementation of the OpenAI GPT training
dotfiles - My dotfiles for vim, bash and others
TFServing-Demos - TF Serving demos