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  ---
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  language:
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  - en
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  tags:
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  - aspect-based-sentiment-analysis
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- - PyABSA
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  license: mit
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  datasets:
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- - laptop14
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- - restaurant14
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- - restaurant16
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- - ACL-Twitter
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- - MAMS
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- - Television
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- - TShirt
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- - Yelp
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  metrics:
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  - accuracy
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  - macro-f1
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-
 
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  ---
 
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  # Note
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  This model is training with 30k+ ABSA samples, see [ABSADatasets](https://github.com/yangheng95/ABSADatasets). Yet the test sets are not included in pre-training, so you can use this model for training and benchmarking on common ABSA datasets, e.g., Laptop14, Rest14 datasets. (Except for the Rest15 dataset!)
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+
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  ---
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  language:
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  - en
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  tags:
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  - aspect-based-sentiment-analysis
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+ - lcf-bert
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  license: mit
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  datasets:
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+ - laptop14 (w/ augmentation)
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+ - restaurant14 (w/ augmentation)
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+ - restaurant16 (w/ augmentation)
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+ - ACL-Twitter (w/ augmentation)
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+ - MAMS (w/ augmentation)
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+ - Television (w/ augmentation)
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+ - TShirt (w/ augmentation)
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+ - Yelp (w/ augmentation)
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  metrics:
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  - accuracy
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  - macro-f1
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+ widget:
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+ - text: "[CLS] when tables opened up, the manager sat another party before us. [SEP] manager [SEP] "
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  ---
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+
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  # Note
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  This model is training with 30k+ ABSA samples, see [ABSADatasets](https://github.com/yangheng95/ABSADatasets). Yet the test sets are not included in pre-training, so you can use this model for training and benchmarking on common ABSA datasets, e.g., Laptop14, Rest14 datasets. (Except for the Rest15 dataset!)
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