readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: finetuned_distilbert_fa_zwnj_base_ner
    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_distilbert_fa_zwnj_base_ner
  
  This model is a fine-tuned version of [HooshvareLab/distilbert-fa-zwnj-base](https://huggingface.co/HooshvareLab/distilbert-fa-zwnj-base) on the mixed NER dataset collected from ARMAN, PEYMA, and WikiANN.
  It achieves the following results on the evaluation set:
  - Loss: 0.0343
  - Precision: 0.9416
  - Recall: 0.9549
  - F1: 0.9482
  - Accuracy: 0.9938
  
  ## 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: 10
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
  |:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | 0.1456        | 1.0   | 1821  | 0.0699          | 0.7847    | 0.8037 | 0.7941 | 0.9773   |
  | 0.0551        | 2.0   | 3642  | 0.0456          | 0.8574    | 0.8875 | 0.8722 | 0.9858   |
  | 0.0283        | 3.0   | 5463  | 0.0333          | 0.8957    | 0.9225 | 0.9089 | 0.9902   |
  | 0.0161        | 4.0   | 7284  | 0.0299          | 0.9229    | 0.9374 | 0.9301 | 0.9921   |
  | 0.0103        | 5.0   | 9105  | 0.0298          | 0.9314    | 0.9471 | 0.9392 | 0.9929   |
  | 0.0069        | 6.0   | 10926 | 0.0323          | 0.9305    | 0.9513 | 0.9408 | 0.9930   |
  | 0.0045        | 7.0   | 12747 | 0.0337          | 0.9363    | 0.9510 | 0.9436 | 0.9933   |
  | 0.0031        | 8.0   | 14568 | 0.0339          | 0.9395    | 0.9526 | 0.9460 | 0.9937   |
  | 0.0024        | 9.0   | 16389 | 0.0334          | 0.9392    | 0.9545 | 0.9468 | 0.9938   |
  | 0.0017        | 10.0  | 18210 | 0.0343          | 0.9416    | 0.9549 | 0.9482 | 0.9938   |
  
  
  ### Framework versions
  
  - Transformers 4.21.2
  - Pytorch 1.12.1+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  