bert-finetuned-ner1

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

• Loss: 0.0493
• Precision: 0.5627
• Recall: 0.3880
• F1: 0.4593
• Accuracy: 0.9888

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: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• training_steps: 5000

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.0677	0.0444	5000	0.0493	0.5627	0.3880	0.4593	0.9888

Framework versions

• Transformers 4.41.1
• Pytorch 2.3.0+cpu
• Datasets 2.19.1
• Tokenizers 0.19.1