siddharthtumre / scibert-finetuned-ner

huggingface.co
Total runs: 5
24-hour runs: 0
7-day runs: -1
30-day runs: -1
Model's Last Updated: August 24 2022
token-classification

Introduction of scibert-finetuned-ner

Model Details of scibert-finetuned-ner

scibert-finetuned-ner

This model is a fine-tuned version of allenai/scibert_scivocab_uncased on the jnlpba dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4717
  • Precision: 0.6737
  • Recall: 0.7757
  • F1: 0.7211
  • Accuracy: 0.9226
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: linear
  • num_epochs: 5
Training results
Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
0.1608 1.0 2319 0.2431 0.6641 0.7581 0.7080 0.9250
0.103 2.0 4638 0.2916 0.6739 0.7803 0.7232 0.9228
0.0659 3.0 6957 0.3662 0.6796 0.7624 0.7186 0.9233
0.0393 4.0 9276 0.4222 0.6737 0.7771 0.7217 0.9225
0.025 5.0 11595 0.4717 0.6737 0.7757 0.7211 0.9226
Framework versions
  • Transformers 4.21.1
  • Pytorch 1.12.1+cu113
  • Datasets 2.4.0
  • Tokenizers 0.12.1

Runs of siddharthtumre scibert-finetuned-ner on huggingface.co

5
Total runs
0
24-hour runs
1
3-day runs
-1
7-day runs
-1
30-day runs

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