readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: BERT_NER_Ep5-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_NER_Ep5-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: 0.3553
  - Precision: 0.6526
  - Recall: 0.7248
  - F1: 0.6868
  - Accuracy: 0.9004
  
  ## 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: 5
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | No log        | 1.0   | 288  | 0.3675          | 0.5906    | 0.5854 | 0.5880 | 0.8802   |
  | 0.4803        | 2.0   | 576  | 0.3456          | 0.5863    | 0.7371 | 0.6531 | 0.8864   |
  | 0.4803        | 3.0   | 864  | 0.3273          | 0.6478    | 0.7091 | 0.6771 | 0.8987   |
  | 0.2233        | 4.0   | 1152 | 0.3441          | 0.6539    | 0.7226 | 0.6865 | 0.9001   |
  | 0.2233        | 5.0   | 1440 | 0.3553          | 0.6526    | 0.7248 | 0.6868 | 0.9004   |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.9.0+cu111
  - Datasets 1.12.1
  - Tokenizers 0.10.3
  