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ner__edgar_all_4-no-valid-roberta-base__roberta-base

This model is a fine-tuned version of roberta-base on the lltala/edgar_all_4-no-valid-roberta-base dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0074
  • Loc Precision: 0.8687
  • Loc Recall: 0.8866
  • Loc F1: 0.8776
  • Loc Number: 97
  • Org Precision: 0.9455
  • Org Recall: 0.9792
  • Org F1: 0.9620
  • Org Number: 673
  • Per Precision: 0.9438
  • Per Recall: 1.0
  • Per F1: 0.9711
  • Per Number: 84
  • Overall Precision: 0.9367
  • Overall Recall: 0.9707
  • Overall F1: 0.9534
  • Overall Accuracy: 0.9982

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
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