finetuned_parsBERT_NER_fa

This model is a fine-tuned version of HooshvareLab/bert-fa-zwnj-base on the mixed NER dataset collected from ARMAN, PEYMA, and WikiANN. It achieves the following results on the evaluation set:

  • Loss: 0.0297
  • Precision: 0.9481
  • Recall: 0.9582
  • F1: 0.9531
  • Accuracy: 0.9942

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: 5

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
0.12 1.0 1821 0.0543 0.8387 0.8577 0.8481 0.9830
0.0381 2.0 3642 0.0360 0.8941 0.9247 0.9091 0.9898
0.0168 3.0 5463 0.0282 0.9273 0.9452 0.9362 0.9927
0.0078 4.0 7284 0.0284 0.9391 0.9551 0.9470 0.9938
0.0033 5.0 9105 0.0297 0.9481 0.9582 0.9531 0.9942

Framework versions

  • Transformers 4.21.2
  • Pytorch 1.12.1+cu113
  • Datasets 2.4.0
  • Tokenizers 0.12.1
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