atsc tk instruct base def pos neg neut combined This model is finetuned for the Aspect Term Sentiment Classification (ATSC) subtask. The finetuning was carried out by adding prompts of the form: definition + 2 positive examples + 2 negative examples + 2 neutral examples The prompt is prepended onto each input review. It is important to note that this model output was finetuned on samples from both laptops and restaurants domains. The code for the official implementation of the paper InstructABSA: Instruction Learning for Aspect Based Sentiment Analysis can be found here. For the ATSC subtask, this model has a competitive performance with the current SOTA. Training data InstructABSA models are trained on the benchmark dataset for Aspect Based Sentiment Analysis tasks viz. SemEval 2014. This dataset consists of reviews from laptops and restaurant domains and their corresponding aspect term and polarity labels. BibTeX entry and citation info If you use this model in your work, please cite the following paper:
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