roberta_large-ner-conll2003_0818_v0

This model is a fine-tuned version of roberta-large on the conll2003 dataset. It achieves the following results on the evaluation set:

• Loss: 0.1793
• Precision: 0.9064
• Recall: 0.9333
• F1: 0.9197
• Accuracy: 0.9796

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: 1e-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
0.0273	1.0	878	0.0500	0.9338	0.9588	0.9461	0.9894
0.0154	2.0	1756	0.0479	0.9402	0.9660	0.9529	0.9904

Framework versions

• Transformers 4.21.1
• Pytorch 1.12.1+cu113
• Datasets 2.4.0
• Tokenizers 0.12.1