SourceData_NER_v1_0_0_PubMedBERT_base

This model is a fine-tuned version of microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract on the source_data dataset. It achieves the following results on the evaluation set:

• Loss: 0.1432
• Accuracy Score: 0.9557
• Precision: 0.8140
• Recall: 0.8536
• F1: 0.8333

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: 0.0001
• train_batch_size: 64
• eval_batch_size: 128
• seed: 42
• optimizer: Use adafactor and the args are: No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 2.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy Score	Precision	Recall	F1
0.1092	1.0	864	0.1403	0.9520	0.8061	0.8293	0.8175
0.075	2.0	1728	0.1432	0.9557	0.8140	0.8536	0.8333

Framework versions

• Transformers 4.46.3
• Pytorch 1.13.1+cu117
• Datasets 3.1.0
• Tokenizers 0.20.3