Add RankNetLoss #7
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Hi @tomaarsen, I've added RankNetLoss. |
tomaarsen
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It's a bit confusing to include the weighting scheme in the config if the RankNet loss doesn't have a notion of that
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I think this is looking great! I'm merging it now 🤗
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Thank you and great work!! |
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RankNetLoss Implementation for Cross Encoder Trainer
This PR adds RankNetLoss functionality to the Cross Encoder Trainer feature.
Changes
Implementation Details
RankNetLoss is a pairwise loss function which learns a ranking function by optimizing pairwise document comparisons using a neural network.
The implementation inherits from the LambdaLoss base class and uses a NoWeightingScheme, focusing solely on the pairwise comparison of documents.
The loss function implements the core RankNet algorithm from the Burges et al. paper (2005), which uses gradient descent to learn a ranking function by optimizing a probabilistic cost function based on pairwise document comparisons.
Reference: https://icml.cc/Conferences/2015/wp-content/uploads/2015/06/icml_ranking.pdf