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README.md
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@@ -3,11 +3,6 @@ library_name: setfit
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tags:
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- setfit
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- absa
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- absa
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- absa
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- absa
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- absa
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- absa
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- sentence-transformers
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- text-classification
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- generated_from_setfit_trainer
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hardware_used: 1 x NVIDIA GeForce RTX 3090
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base_model: BAAI/bge-small-en-v1.5
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model-index:
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- name: SetFit Polarity Model
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Model Polarity Model with BAAI/bge-small-en-v1.5
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results:
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- task:
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type: text-classification
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name: Text Classification
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dataset:
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name: Unknown
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type: unknown
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split: test
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metrics:
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- type: accuracy
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value: 0.7260223048327138
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name: Accuracy
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---
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# SetFit Polarity Model
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This is a [SetFit](https://github.com/huggingface/setfit) model that can be used for Aspect Based Sentiment Analysis (ABSA). This SetFit model uses [BAAI/bge-small-en-v1.5](https://huggingface.co/BAAI/bge-small-en-v1.5) as the Sentence Transformer embedding model. A [LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) instance is used for classification. In particular, this model is in charge of classifying aspect polarities.
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tags:
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- setfit
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- absa
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- sentence-transformers
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- text-classification
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- generated_from_setfit_trainer
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hardware_used: 1 x NVIDIA GeForce RTX 3090
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base_model: BAAI/bge-small-en-v1.5
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model-index:
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- name: SetFit Polarity Model with BAAI/bge-small-en-v1.5
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results:
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- task:
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type: text-classification
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name: Text Classification
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metrics:
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- type: accuracy
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value: 0.7260223048327138
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name: Accuracy
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---
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# SetFit Polarity Model with BAAI/bge-small-en-v1.5
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This is a [SetFit](https://github.com/huggingface/setfit) model that can be used for Aspect Based Sentiment Analysis (ABSA). This SetFit model uses [BAAI/bge-small-en-v1.5](https://huggingface.co/BAAI/bge-small-en-v1.5) as the Sentence Transformer embedding model. A [LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) instance is used for classification. In particular, this model is in charge of classifying aspect polarities.
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