safetensors distilbert text-classification en dataset:gexai/inquisitiveqg base_model:distilbert/distilbert-base-uncased base_model:finetune:distilbert/distilbert-base-uncased license:apache-2.0 region:us
---
base_model:
- distilbert/distilbert-base-uncased
datasets:
- gexai/inquisitiveqg
language:
- en
license: apache-2.0
metrics:
- accuracy
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,