Using the sentence transformers you have provided I tried different variations for the aspect model and the polarity model and obtained good results.
However I am interested in two more things which I tried and still couldn't achieve.
1) For ABSA tasks rather than three labels I wanted to expand it to 5, adding the more positive and more negative parts. We manually annotated our own dataset for this as for the format of the Laptop and restaurant 14 datasets you have provided. But it did not give the expected results. The polarities cannot be expanded to 5. How can I achieve this ? Can you guide on this matter.
2) Instead of the accuracies for the Polarity and aspect extraction separately I want an collective accuracy. A single accuracy that represents both. How can I do that?
Using the sentence transformers you have provided I tried different variations for the aspect model and the polarity model and obtained good results. However I am interested in two more things which I tried and still couldn't achieve.
1) For ABSA tasks rather than three labels I wanted to expand it to 5, adding the more positive and more negative parts. We manually annotated our own dataset for this as for the format of the Laptop and restaurant 14 datasets you have provided. But it did not give the expected results. The polarities cannot be expanded to 5. How can I achieve this ? Can you guide on this matter.
2) Instead of the accuracies for the Polarity and aspect extraction separately I want an collective accuracy. A single accuracy that represents both. How can I do that?