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README.md
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- feature-extraction
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- sentence-similarity
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- transformers
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---
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# econosentence
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This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
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## Usage (Sentence-Transformers)
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## Evaluation Results
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For an automated evaluation of this model, see the *Sentence Embeddings Benchmark*: [https://seb.sbert.net](https://seb.sbert.net?model_name=econosentence)
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- feature-extraction
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- sentence-similarity
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- transformers
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datasets:
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- samchain/econo-pairs
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language:
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- en
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metrics:
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- pearsonr
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library_name: sentence-transformers
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---
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# econosentence
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This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
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Econosentence can be used fro various tasks in NLP applied to economics. The main one is to use embeddings for topic modeling purpose.
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## Usage (Sentence-Transformers)
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## Evaluation Results
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The Pearson correlation for the train test is : 0.83
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For an automated evaluation of this model, see the *Sentence Embeddings Benchmark*: [https://seb.sbert.net](https://seb.sbert.net?model_name=econosentence)
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