readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: finetuned_parsBERT_NER_fa
    results: []
  ---
  
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
  should probably proofread and complete it, then remove this comment. -->
  
  # finetuned_parsBERT_NER_fa
  
  This model is a fine-tuned version of [HooshvareLab/bert-fa-zwnj-base](https://huggingface.co/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
  