readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: bert-finetuned-ner2
    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-ner2
  
  This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0015
  - Precision: 0.9709
  - Recall: 0.9904
  - F1: 0.9806
  - Accuracy: 0.9995
  
  ## 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: 5
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | No log        | 1.0   | 108  | 0.0035          | 0.9565    | 0.9876 | 0.9718 | 0.9990   |
  | No log        | 2.0   | 216  | 0.0019          | 0.9628    | 0.9904 | 0.9764 | 0.9994   |
  | No log        | 3.0   | 324  | 0.0016          | 0.9764    | 0.9904 | 0.9834 | 0.9995   |
  | No log        | 4.0   | 432  | 0.0017          | 0.9736    | 0.9866 | 0.9801 | 0.9995   |
  | 0.0166        | 5.0   | 540  | 0.0015          | 0.9709    | 0.9904 | 0.9806 | 0.9995   |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.12.1+cu113
  - Datasets 2.6.1
  - Tokenizers 0.13.2
  