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bert-base-NER-finetuned-ner

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metadata
license: mit
base_model: surrey-nlp/roberta-base-finetuned-abbr
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: bert-base-NER-finetuned-ner
    results: []

bert-base-NER-finetuned-ner

This model is a fine-tuned version of surrey-nlp/roberta-base-finetuned-abbr on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4944
  • Precision: 0.8197
  • Recall: 0.8510
  • F1: 0.8350
  • Accuracy: 0.8172

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: 8
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 20
  • mixed_precision_training: Native AMP

Training results

Framework versions

  • Transformers 4.37.2
  • Pytorch 2.2.2+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.1