readme: ---
  license: apache-2.0
  tags:
  - generated_from_keras_callback
  model-index:
  - name: ohss117/bert-finetuned-ner_v2
    results: []
  ---
  
  <!-- This model card has been generated automatically according to the information Keras had access to. You should
  probably proofread and complete it, then remove this comment. -->
  
  # ohss117/bert-finetuned-ner_v2
  
  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:
  - Train Loss: 0.0003
  - Validation Loss: 0.0919
  - Epoch: 21
  
  ## 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:
  - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 21950, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
  - training_precision: mixed_float16
  
  ### Training results
  
  | Train Loss | Validation Loss | Epoch |
  |:----------:|:---------------:|:-----:|
  | 0.1785     | 0.0609          | 0     |
  | 0.0493     | 0.0581          | 1     |
  | 0.0288     | 0.0621          | 2     |
  | 0.0187     | 0.0581          | 3     |
  | 0.0141     | 0.0630          | 4     |
  | 0.0096     | 0.0665          | 5     |
  | 0.0060     | 0.0735          | 6     |
  | 0.0064     | 0.0774          | 7     |
  | 0.0055     | 0.0717          | 8     |
  | 0.0028     | 0.0796          | 9     |
  | 0.0020     | 0.0913          | 10    |
  | 0.0024     | 0.0787          | 11    |
  | 0.0023     | 0.0877          | 12    |
  | 0.0024     | 0.0793          | 13    |
  | 0.0010     | 0.0873          | 14    |
  | 0.0008     | 0.0874          | 15    |
  | 0.0013     | 0.0902          | 16    |
  | 0.0007     | 0.0925          | 17    |
  | 0.0005     | 0.0957          | 18    |
  | 0.0005     | 0.0914          | 19    |
  | 0.0004     | 0.0926          | 20    |
  | 0.0003     | 0.0919          | 21    |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - TensorFlow 2.10.1
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  