Adam-NER-Model / README.md
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metadata
license: mit
base_model: dslim/bert-large-NER
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: Adam-NER-Model
    results: []
datasets:
  - conll2003
  - rungalileo/mit_movies
  - hyperhustle/ner-dataset
language:
  - en
pipeline_tag: token-classification

bert-finetuned-ner-adam

This model is a fine-tuned version of dslim/bert-large-NER on an hyperhustle/ner-dataset dataset. It achieves the following results on the evaluation set:

  • Loss: nan
  • Precision: 0.8845
  • Recall: 0.8749
  • F1: 0.8797
  • Accuracy: 0.9646

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: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 3

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
0.0949 1.0 3080 nan 0.8914 0.8942 0.8928 0.9663
0.0574 2.0 6160 nan 0.8763 0.8784 0.8773 0.9635
0.0376 3.0 9240 nan 0.8845 0.8749 0.8797 0.9646

Framework versions

  • Transformers 4.38.2
  • Pytorch 2.1.0+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2