Shypd.aiThe largest open index of AI toolsallRank is an open-source framework for training neural Learning-to-Rank (LTR) models using PyTorch. It provides implementations of common loss functions, scoring functions, and evaluation metrics like NDCG and MRR.
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allRank is a PyTorch-based, open-source framework designed for training neural Learning-to-Rank (LTR) models. It offers a flexible environment for experimenting with various LTR neural network models and loss functions, making it easy to add custom losses and configure models and training procedures. The framework includes implementations of common pointwise, pairwise, and listwise loss functions such as ListNet, RankNet, LambdaRank, and NeuralNDCG. It also features fully connected and Transformer-like scoring functions, alongside widely used evaluation metrics like Normalized Discounted Cumulative Gain (NDCG) and Mean Reciprocal Rank (MRR). Additionally, allRank supports click-models for experiments on simulated click-through data and integrates with Google Cloud Storage for data and job results, facilitating both research and industrial applications in neural LTR.
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