speediedan/deep_classiflie
Deep Classiflie is a framework for developing ML models that bolster fact-checking efficiency. As a POC, the initial alpha release of Deep Classiflie generates/analyzes a model that continuously classifies a single individual's statements (Donald Trump) using a single ground truth labeling source (The Washington Post). For statements the model deems most likely to be labeled falsehoods, the @DeepClassiflie twitter bot tweets out a statement analysis and model interpretation "report"
Python
Issues
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Write actual README
#5 opened by speediedan - 0
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Replicate best existing model with Context-Dependent Attention Pipeline Enhancement
#2 opened by speediedan - 0
Add model analysis/viz notebook to repo
#7 opened by speediedan - 0
Validate/Document SWA Checkpoint Structure
#3 opened by speediedan - 0
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Remove dropout and check for overfiitting
#28 opened by speediedan - 0
Use all dims for cos sim, then PCA on (top y similar words) x full dim matrix, plot 1st PCA dim of PCA matrix
#29 opened by speediedan - 0
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Compare filtering top k cos sim of mlm context aware output vector for max attr word instead of raw bert embedding
#26 opened by speediedan - 0
train from scratch with tweet-only dataset
#27 opened by speediedan - 0
Bucket all predictions
#24 opened by speediedan - 0
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fix ellipses generation on report
#21 opened by speediedan - 0
auto-remove intermediate files
#22 opened by speediedan - 0
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fix global step float type issue
#18 opened by speediedan - 0
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refactor deep_classiflie config files
#15 opened by speediedan - 0
refactor deep_classiflie analysis modules
#16 opened by speediedan - 0
debug device number ref
#17 opened by speediedan - 0
refactor deep_classiflie training modules
#12 opened by speediedan - 0
refactor deep_classiflie models modules
#13 opened by speediedan - 0
refactor deep_classiflie dataprep modules
#14 opened by speediedan - 0
refactor deep_classiflie utils modules
#11 opened by speediedan