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ner-2-roberta-base

This model is a fine-tuned version of roberta-base on the lltala/e-ner-roberta-base dataset. It achieves the following results on the evaluation set:

• Loss: 0.0798
• Loc Precision: 0.625
• Loc Recall: 0.7216
• Loc F1: 0.6699
• Loc Number: 97
• Org Precision: 0.8401
• Org Recall: 0.6716
• Org F1: 0.7465
• Org Number: 673
• Per Precision: 0.9425
• Per Recall: 0.9762
• Per F1: 0.9591
• Per Number: 84
• Overall Precision: 0.8195
• Overall Recall: 0.7073
• Overall F1: 0.7593
• Overall Accuracy: 0.9854

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: 5e-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: 3.0

Training results

Framework versions

• Transformers 4.35.0.dev0
• Pytorch 2.1.0+cu118
• Datasets 2.14.6
• Tokenizers 0.14.1