What are annotation guidelines? What are inter-annotator agreement metrics?

Abstract. Bidirectional Encoder Representations from Transformers (BERT) and BERT-based approaches are the current state-of-the-art in many natural language ... default=None, metadata={"help": "The name of the dataset to use (via the datasets library)."} ) dataset_config_name ... Apr 3, 2025 ... Text classification is a key natural language processing task widely used in areas such as news classification, sentiment analysis, topic ... May 1, 2020 ... We hypothesize that the application of different combinations of preprocessing methods can improve TC results. The AutoKeras TextClassifier is quite flexible for the data format. For the text, the input data should be one-dimensional. Mar 29, 2024 ... Text data augmentation and pre-trained Language Model for enhancing text classification of low-resource languages Dec 24, 2022 ... In this post we'll see a demonstration of an NLP-Classification problem with 2 different approaches in python. Summary. Trains a single or multilabel text classification model to assign a predefined category or label to unstructured text. Learn more about how Text ... Our experiments have shown that both approaches can interact with LLMs successfully to classify text—if certain criteria are met ... Jul 21, 2024 ... This tutorial on Fine tuning LLama 3 LLM for Text Classification of Stock Sentiment using QLoRA was particularly useful.