bert-finetuned-ner

This model is a fine-tuned version of bert-base-cased on the conll2003 dataset.

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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	50	0.7066	0.0	0.0	0.0	0.7985

Framework versions

• Transformers 4.49.0
• Pytorch 2.6.0+cpu
• Datasets 3.3.2
• Tokenizers 0.21.0