readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: bert-finetuned-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. -->
  
  # bert-finetuned-ner
  
  This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1196
  - Precision: 0.7872
  - Recall: 0.8292
  - F1: 0.8077
  - Accuracy: 0.9722
  
  ## 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: 4
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | 0.1243        | 1.0   | 1380 | 0.0932          | 0.6752    | 0.8222 | 0.7415 | 0.9635   |
  | 0.0624        | 2.0   | 2760 | 0.0890          | 0.7298    | 0.8368 | 0.7797 | 0.9686   |
  | 0.0405        | 3.0   | 4140 | 0.1029          | 0.7792    | 0.8356 | 0.8064 | 0.9715   |
  | 0.0226        | 4.0   | 5520 | 0.1196          | 0.7872    | 0.8292 | 0.8077 | 0.9722   |
  
  
  ### Framework versions
  
  - Transformers 4.12.5
  - Pytorch 1.10.0+cu111
  - Datasets 1.15.1
  - Tokenizers 0.10.3
  