Hugging Face's logo

KevSun
/
Engessay_grading_ML

Text Classification
Transformers
PyTorch
roberta
text-embeddings-inference
Model card Files
xet
 Community
2
KevSun commited on
Commit
43cda42
·
verified ·
1 Parent(s): 429ba2a

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +1 -1
README.md CHANGED
@@ -13,7 +13,7 @@ is summarized by the following metrics: 'mean accuracy'= 0.91 and 'mean f1 score
13
 
14
  Upon inputting an essay, the model outputs six scores corresponding to cohesion, syntax, vocabulary, phraseology, grammar, and conventions. Each score ranges from 1 to 5, with higher scores indicating greater proficiency within the essay. These dimensions collectively assess the quality of the input essay from multiple perspectives. The model serves as a valuable tool for EFL teachers and researchers, and it is also beneficial for English L2 learners and parents for self-evaluating their composition skills.
15
 
16
- You can get scores after inputing your essay here: [https://huggingface.co/spaces/KevSun/MultiDim_Automated_Scoring_English_Essays].
17
 
18
  Please **cite** the following paper if you use this model:
19
  ```
 
13
 
14
  Upon inputting an essay, the model outputs six scores corresponding to cohesion, syntax, vocabulary, phraseology, grammar, and conventions. Each score ranges from 1 to 5, with higher scores indicating greater proficiency within the essay. These dimensions collectively assess the quality of the input essay from multiple perspectives. The model serves as a valuable tool for EFL teachers and researchers, and it is also beneficial for English L2 learners and parents for self-evaluating their composition skills.
15
 
16
+ You can get scores after inputing your essay in this [App]: (https://huggingface.co/spaces/KevSun/MultiDim_Automated_Scoring_English_Essays).
17
 
18
  Please **cite** the following paper if you use this model:
19
  ```