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Legal-BERTimbau-sts-large

Sentence Similarity sentence-transformers PyTorch Transformers
Portuguese bert feature-extraction Eval Results Inference Endpoints
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@@ -84,22 +84,23 @@ print("Sentence embeddings:")
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  print(sentence_embeddings)
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  ```
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  ## Evaluation Results STS
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- | Model| Assin | Assin2|stsb_multi_mt pt|
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- | ---------------------------------------- | ---------- | ---------- |---------- |
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- | Legal-BERTimbau-sts-base| 0.71457| 0.73545 | 0.72383|
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- | Legal-BERTimbau-sts-base-ma| 0.74874 | 0.79532|0.82254 |
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- | Legal-BERTimbau-sts-base-ma-v2| 0.75481 | 0.80262|0.82178|
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- | Legal-BERTimbau-sts-large| 0.76629| 0.82357 | 0.79120|
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- | Legal-BERTimbau-sts-large-v2| 0.76299 | 0.81121|0.81726 |
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- | Legal-BERTimbau-sts-large-ma| 0.76195| 0.81622 | 0.82608|
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- | Legal-BERTimbau-sts-large-ma-v2| 0.7836| 0.8462| 0.8261|
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- | Legal-BERTimbau-sts-large-ma-v3| 0.7749| 0.8470| 0.8364|
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- | ---------------------------------------- | ---------- |---------- |---------- |
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- | BERTimbau base Fine-tuned for STS|0.78455 | 0.80626|0.82841|
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- | BERTimbau large Fine-tuned for STS|0.78193 | 0.81758|0.83784|
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- | ---------------------------------------- | ---------- |---------- |---------- |
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- | paraphrase-multilingual-mpnet-base-v2| 0.71457| 0.79831 |0.83999 |
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- | paraphrase-multilingual-mpnet-base-v2 Fine-tuned with assin(s)| 0.77641|0.79831 |0.84575 |
 
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  ## Training
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  rufimelo/Legal-BERTimbau-sts-large is based on Legal-BERTimbau-large which derives from [BERTimbau](https://huggingface.co/neuralmind/bert-base-portuguese-cased) large.
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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) and [assin2](https://huggingface.co/datasets/assin2) datasets.
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  print(sentence_embeddings)
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  ```
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  ## Evaluation Results STS
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+
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+ | Model| Assin | Assin2|stsb_multi_mt pt| avg|
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+ | ---------------------------------------- | ---------- | ---------- |---------- |---------- |
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+ | Legal-BERTimbau-sts-base| 0.71457| 0.73545 | 0.72383|0.72462|
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+ | Legal-BERTimbau-sts-base-ma| 0.74874 | 0.79532|0.82254 |0.78886|
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+ | Legal-BERTimbau-sts-base-ma-v2| 0.75481 | 0.80262|0.82178|0.79307|
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+ | Legal-BERTimbau-sts-large| 0.76629| 0.82357 | 0.79120|0.79369|
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+ | Legal-BERTimbau-sts-large-v2| 0.76299 | 0.81121|0.81726 |0.79715|
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+ | Legal-BERTimbau-sts-large-ma| 0.76195| 0.81622 | 0.82608|0.80142|
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+ | Legal-BERTimbau-sts-large-ma-v2| 0.7836| 0.8462| 0.8261| 0.81863|
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+ | Legal-BERTimbau-sts-large-ma-v3| 0.7749| **0.8470**| 0.8364| **0.81943**|
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+ | ---------------------------------------- | ---------- |---------- |---------- |---------- |
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+ | BERTimbau base Fine-tuned for STS|**0.78455** | 0.80626|0.82841|0.80640|
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+ | BERTimbau large Fine-tuned for STS|0.78193 | 0.81758|0.83784|0.81245|
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+ | ---------------------------------------- | ---------- |---------- |---------- |---------- |
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+ | paraphrase-multilingual-mpnet-base-v2| 0.71457| 0.79831 |0.83999 |0.78429|
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+ | paraphrase-multilingual-mpnet-base-v2 Fine-tuned with assin(s)| 0.77641|0.79831 |**0.84575**|0.80682|
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  ## Training
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  rufimelo/Legal-BERTimbau-sts-large is based on Legal-BERTimbau-large which derives from [BERTimbau](https://huggingface.co/neuralmind/bert-base-portuguese-cased) large.
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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) and [assin2](https://huggingface.co/datasets/assin2) datasets.