bert-base-uncased-Q_and_A-Answer_Prediction_Dataset

This model is a fine-tuned version of bert-base-uncased.

Model description

This is an extractive question answer model.

For more information on how it was created, check out the following link: https://github.com/DunnBC22/NLP_Projects/blob/main/Question%26Answer/Answer%20Prediction%20Dataset%20-%20Question%26Answer%20with%20BERT.ipynb

Intended uses & limitations

This model is intended to demonstrate my ability to solve a complex problem using technology.

Training and evaluation data

Dataset Source: https://www.kaggle.com/datasets/a2m2a2n2/question-answer-dataset

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 2e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3

Training results

Framework versions

• Transformers 4.26.1
• Pytorch 1.12.1
• Datasets 2.8.0
• Tokenizers 0.12.1