AnswerBERT_model

This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.2301
• Accuracy: 0.9413

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

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: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.1391	1.0	36170	0.2255	0.9236
0.0989	2.0	72340	0.2301	0.9413

Framework versions

• Transformers 4.26.1
• Pytorch 1.13.0
• Datasets 2.6.1
• Tokenizers 0.11.0