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@@ -54,7 +54,7 @@ Thesis: [A Semantic Search System for Supremo Tribunal de Justiça](https://rufi
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This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 1024 dimensional dense vector space and can be used for tasks like clustering or semantic search.
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stjiris/bert-large-portuguese-cased-legal-mlm-nli-sts-v1 derives from stjiris/bert-large-portuguese-cased-legal-mlm (legal variant of [BERTimbau](https://huggingface.co/neuralmind/bert-large-portuguese-cased) large).
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It was trained using the MLM technique with a learning rate 1e-5 [Legal Sentences from +-30000 documents](https://huggingface.co/datasets/stjiris/portuguese-legal-sentences-v1.0)
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The model was presented to NLI data. 16 batch size, 2e-5 lr
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This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 1024 dimensional dense vector space and can be used for tasks like clustering or semantic search.
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stjiris/bert-large-portuguese-cased-legal-mlm-nli-sts-v1 derives from stjiris/bert-large-portuguese-cased-legal-mlm (legal variant of [BERTimbau](https://huggingface.co/neuralmind/bert-large-portuguese-cased) large).
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It was trained using the MLM technique with a learning rate 1e-5 [Legal Sentences from +-30000 documents](https://huggingface.co/datasets/stjiris/portuguese-legal-sentences-v1.0) 15000 training steps (best performance for our semantic search system implementation)
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The model was presented to NLI data. 16 batch size, 2e-5 lr
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