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README.md
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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-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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It was trained for Semantic Textual Similarity, being submitted to a fine tuning stage with the [assin](https://huggingface.co/datasets/assin), [assin2](https://huggingface.co/datasets/assin2), [stsb_multi_mt pt](https://huggingface.co/datasets/stsb_multi_mt) and [IRIS STS](https://huggingface.co/datasets/stjiris/IRIS_sts) datasets. 'lr': 1e-5
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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-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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It was trained for Semantic Textual Similarity, being submitted to a fine tuning stage with the [assin](https://huggingface.co/datasets/assin), [assin2](https://huggingface.co/datasets/assin2), [stsb_multi_mt pt](https://huggingface.co/datasets/stsb_multi_mt) and [IRIS STS](https://huggingface.co/datasets/stjiris/IRIS_sts) datasets. 'lr': 1e-5
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