Gladiator / roberta-large_ner_conll2003

huggingface.co
Total runs: 5.3K
24-hour runs: -251
7-day runs: 554
30-day runs: 1.4K
Model's Last Updated: December 09 2022
token-classification

Introduction of roberta-large_ner_conll2003

Model Details of roberta-large_ner_conll2003

roberta-large_ner_conll2003

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

  • Loss: 0.0345
  • Precision: 0.9622
  • Recall: 0.9692
  • F1: 0.9657
  • Accuracy: 0.9939
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: cosine
  • num_epochs: 5
Training results
Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
0.1227 1.0 878 0.0431 0.9511 0.9559 0.9535 0.9914
0.0295 2.0 1756 0.0334 0.9541 0.9657 0.9599 0.9930
0.0163 3.0 2634 0.0327 0.9616 0.9682 0.9649 0.9938
0.0073 4.0 3512 0.0342 0.9624 0.9692 0.9658 0.9939
0.0042 5.0 4390 0.0345 0.9622 0.9692 0.9657 0.9939
Framework versions
  • Transformers 4.20.1
  • Pytorch 1.11.0
  • Datasets 2.1.0
  • Tokenizers 0.12.1

Runs of Gladiator roberta-large_ner_conll2003 on huggingface.co

5.3K
Total runs
-251
24-hour runs
-122
3-day runs
554
7-day runs
1.4K
30-day runs

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