You will get Develop BERT Question Answering model explanations with visualization
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Project details
Client: A Leading Tech Firm in the USA
Industry Type: IT Consulting
Services: Software, Consulting
Organization Size: 100+
Project Description
We need to use a pre-trained bert question answering model and create a notebook that has explanations of model’s working with some visuals of bertviz, allennlp and gradient values.
Our Solution
We created a notebook first and explained the model with model view and head view visuals of bertviz library. It gives similarity between words so we can easily find related words. We used the allennlp library and created bar charts and heatmaps to show higher and lower attention words. It means when it finds question related words in the context it gives higher value to those words and if words are not related it gives lower values.
Project Deliverables
A notebook which has an explanation of the bert question answering model using some visualization.
Tools
Google colab notebooks, Tensorflow, Bertviz, Allennlp, Transformers
Language/techniques
Python, Deep learning, NLP, Data Visualization
Models
Pretrained bert-base-uncased model and distilbert model (both trained on squad2 dataset)
Skills
Data visualization, Deep learning, NLP, python
Industry Type: IT Consulting
Services: Software, Consulting
Organization Size: 100+
Project Description
We need to use a pre-trained bert question answering model and create a notebook that has explanations of model’s working with some visuals of bertviz, allennlp and gradient values.
Our Solution
We created a notebook first and explained the model with model view and head view visuals of bertviz library. It gives similarity between words so we can easily find related words. We used the allennlp library and created bar charts and heatmaps to show higher and lower attention words. It means when it finds question related words in the context it gives higher value to those words and if words are not related it gives lower values.
Project Deliverables
A notebook which has an explanation of the bert question answering model using some visualization.
Tools
Google colab notebooks, Tensorflow, Bertviz, Allennlp, Transformers
Language/techniques
Python, Deep learning, NLP, Data Visualization
Models
Pretrained bert-base-uncased model and distilbert model (both trained on squad2 dataset)
Skills
Data visualization, Deep learning, NLP, python
AI Development Type
Deep Learning, Knowledge Representation, Model Tuning, Recommendation System, Software MaintenanceAI Tools
Azure Machine Learning, deeplearn.js, Keras, MLflow, NVIDIA AI Platform, OpenCV, PyBrain, PyTorch, Sonnet, TensorFlowAI Development Language
PythonWhat's included
| Service Tiers |
Starter
$50
|
Standard
$400
|
Advanced
$2,000
|
|---|---|---|---|
| Delivery Time | 1 day | 10 days | 30 days |
Number of Revisions | 1 | 1 | 2 |
AI Model Integration | |||
Detailed Code Comments | |||
Knowledge Graph | |||
Model Documentation | |||
Ontology | |||
Source Code | |||
Taxonomy |
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DF
Danisavage F.
Aug 14, 2025
Spam detection and email analytics dashboard
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Develop BERT Question Answering model
We need to use a pre-trained bert question answering model and create a notebook that has explanations of model’s working with some visuals of bertviz, allennlp and gradient values.