bert-large-uncased-whole-word-masking-finetuned-policy-named-insured

This model is a fine-tuned version of bert-large-uncased-whole-word-masking-finetuned-squad on the policies-named-insured dataset. It achieves the following results on the evaluation set:

• Loss: 0.0264

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: 3

Training results

Training Loss	Epoch	Step	Validation Loss
No log	1.0	478	0.0402
0.0557	2.0	956	0.0326
0.0106	3.0	1434	0.0264

Framework versions

• Transformers 4.25.1
• Pytorch 1.12.1
• Datasets 2.8.0
• Tokenizers 0.13.2