roberta_large-unbalanced_simple-ner-conll2003_0908_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: 0.0881
• Precision: 0.9553
• Recall: 0.9718
• F1: 0.9635
• Accuracy: 0.9892

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
0.07	1.0	878	0.0249	0.9616	0.9746	0.9681	0.9936
0.0176	2.0	1756	0.0241	0.9699	0.9818	0.9758	0.9948

Framework versions

• Transformers 4.21.3
• Pytorch 1.12.1+cu113
• Datasets 2.4.0
• Tokenizers 0.12.1