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--- |
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tags: |
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- text-classification |
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widget: |
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- text: "Hello! I'm BERT-Grader! I'm a finetuned BERT model for grading user input on values like consistency, grammar and quality!" |
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example_title: "Example 1" |
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library_name: transformers |
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pipeline_tag: text-classification |
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--- |
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# BERT-GRADER? |
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BERT-Grader is a BERT model designed for grading text by mesuring gramar, consistency and quality. |
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Due to an error in the dataset, 'undefined' is 0. |
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BERT-Grader is a finetune of distil-bert, for performance. |
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## Classes |
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0 (Undefined) - Elementary |
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1 - Intermidiate |
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2 - Advanced |
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## Biases and Issues |
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For BERT-Grader to perform well, the input text should be an actual essay. |
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Some biases may arise due to training data phrases, but there were mesures in place to limit bias. |
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Giberrish is accounted for, and will be rather random. I suggest using a spell-checker with this model, and mesure tokens. |
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|
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## Validation Metrics |
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loss: 0.166 |
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accuracy: 0.933333.. |
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# Citing |
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``` |
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@misc {intone_2023, |
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author = { {intone} }, |
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title = { BERT-GRADER (Revision 6bddc72) }, |
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year = 2023, |
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url = { https://huggingface.co/intone/BERT-GRADER }, |
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doi = { 10.57967/hf/1257 }, |
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publisher = { Hugging Face } |
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} |
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``` |
