| | --- |
| | license: apache-2.0 |
| | datasets: |
| | - gexai/inquisitiveqg |
| | language: |
| | - en |
| | metrics: |
| | - accuracy |
| | base_model: |
| | - distilbert/distilbert-base-uncased |
| | pipeline_tag: text-classification |
| | --- |
| | |
| | ## Model Details |
| | Text classification model for ambiguity in questions. Classifies questions as ambiguous or clear. |
| | Based on distilbert/distilbert-base-uncased. |
| |
|
| | **Example:** |
| |
|
| | "Did he do it?" {'label': 'AMBIG', 'score': 0.9029870629310608} |
| |
|
| | "Did Peter win the game?" {'label': 'CLEAR', 'score': 0.8900136351585388} |
| |
|
| | ## Out-of-Scope Use |
| | The model was only trained to classify single questions. Other kinds of data are not tested. |
| |
|
| | ### Training Data |
| | I manually labeled a small part of the inquisitiveqg dataset mixed with a private dataset to train the model to recognize ambiguity in questions. A satisfactory model with 85.5% accuracy was created. |
| |
|
| | #### Metrics |
| | "eval_accuracy": 0.8551401869158879, |
| | |
| | "eval_loss": 0.3658725619316101, |
