distilbert-NER-conll2003

This model is a fine-tuned version of dslim/distilbert-NER on the conll2003 dataset. It achieves the following results on the evaluation set:

• Loss: nan
• Precision: 0.8732
• Recall: 0.8964
• F1: 0.8847
• Accuracy: 0.9751

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
0.0605	1.0	3922	nan	0.8717	0.8877	0.8796	0.9742
0.0296	2.0	7844	nan	0.8732	0.8964	0.8847	0.9751

Framework versions

• Transformers 4.33.2
• Pytorch 2.2.2
• Datasets 2.20.0
• Tokenizers 0.13.3