bert-base-uncased-finetuned-squad_v2

This model is a fine-tuned version of bert-base-uncased on the SQuAD2.0 dataset. It's been trained on question-answer pairs, including unanswerable questions, for the task of Question Answering.

It achieves the following results on the evaluation set:

• Loss: 1.7075
• Exact Match: 71.6920
• F1-score: 75.4437

Overview

Language model: bert-base-uncased
Language: English
Downstream-task: Extractive QA
Training data: SQuAD 2.0
Eval data: SQuAD 2.0

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 2e-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss
1.0593	1.0	8235	1.1296
0.7736	2.0	16470	1.1290
0.5682	3.0	24705	1.1725
0.4124	4.0	32940	1.4632
0.3137	5.0	41175	1.7075

Framework versions

• Transformers 4.34.0
• Pytorch 1.12.1
• Datasets 2.14.5
• Tokenizers 0.14.1