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README.md
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# ate_tk-instruct-base-def-pos-neg-neut-combined
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This model is finetuned for the Aspect Term Extraction (ATE) subtask. The finetuning was carried out by adding prompts of the form:
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- definition + 2 positive examples + 2 negative examples + 2 neutral examples
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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.**
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The code for the official implementation of the paper [**InstructABSA: Instruction Learning for Aspect Based Sentiment Analysis**](https://arxiv.org/abs/2302.08624) can be
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# ate_tk-instruct-base-def-pos-neg-neut-combined
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This model is finetuned for the Aspect Term Extraction (ATE) subtask. The finetuning was carried out by adding prompts of the form:
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+
- definition + 2 positive examples + 2 negative examples + 2 neutral examples
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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.**
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The code for the official implementation of the paper [**InstructABSA: Instruction Learning for Aspect Based Sentiment Analysis**](https://arxiv.org/abs/2302.08624) can be
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