bert-base-uncased-finetuned-ner

This model is a fine-tuned version of bert-base-uncased on the biobert_json dataset. It achieves the following results on the evaluation set:

• Loss: 0.1050
• Precision: 0.9295
• Recall: 0.9664
• F1: 0.9476
• Accuracy: 0.9731

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	Precision	Recall	F1	Accuracy
0.4544	1.0	612	0.1204	0.9242	0.9569	0.9403	0.9698
0.146	2.0	1224	0.1050	0.9295	0.9664	0.9476	0.9731

Framework versions

• Transformers 4.44.2
• Pytorch 2.5.0+cu121
• Datasets 3.1.0
• Tokenizers 0.19.1