contrastive-learning
- Sentence Transformer Fine-Tuning - SetFit (23 Oct 2023)
How SetFit tackles few-shot text classification, fine-tuning a sentence-transformer through contrastive learning on a small number of text pairs before training a classification head.
retrieval-augmented-generation Haystack viterbi sequence-prediction evaluation-metrics scikit-learn pos-tags named-entity-recognition embeddings conditional-random-fields classification word2vec triplet-loss syntactic-dependencies sentence-transformers relationship-extraction neural-networks information-retrieval fine-tuning coursera conference SyntaxNet NLTK LSTM wikidata transformers tokenization tf-idf text-summarisation semantic-web semantic-drift resources reference-post production portuguese political-science naive-bayes multi-label-classification monitoring mlops metadata-extraction maximum-entropy-markov-models logistic-regression llms language-models information-extraction imbalanced-data hyperparameter-optimization hidden-markov-models grid-search gensim generative-ai fasttext document-classification doc2vec deployment dependency-graph dataset data-challenge convolutional-neural-networks contrastive-learning books attention SPARQL RNN PyData KONVENS GRU