bkai foundation models/vietnamese bi encoder This is a sentence transformers model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search. We train the model on a merged training dataset that consists of: MS Macro (translated into Vietnamese) SQuAD v2 (translated into Vietnamese) 80% of the training set from the Legal Text Retrieval Zalo 2021 challenge We use phobert base v2 as the pre trained backbone. Here are the results on the remaining 20% of the training set from the Legal Text Retrieval Zalo 2021 challenge: Pretrained Model Training Datasets Acc@1 Acc@10 Acc@100 Pre@10 MRR@10 : : : : : : : : : : Vietnamese SBERT 32.34 52.97 89.84 7.05 45.30 PhoBERT base v2 MSMACRO 47.81 77.19 92.34 7.72 58.37 PhoBERT base v2 MSMACRO + SQuADv2.0 + 80% Zalo 73.28 93.59 98.85 9.36 80.73 Usage (Sentence Transformers) Using this model becomes easy when you have sentence transformers installed: Then you can use the model like this: Usage (Widget HuggingFace) The widget use custom pipeline on top of the default pipeline by adding additional word segmenter before PhobertTokenizer. So you do not need to segment words before…
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