readme: ---
  license: apache-2.0
  tags:
  - generated_from_keras_callback
  model-index:
  - name: notmaineyy/distilbert-base-uncased-finetuned-ner
    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. -->
  
  # notmaineyy/distilbert-base-uncased-finetuned-ner
  
  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Train Loss: 0.0344
  - Validation Loss: 0.0633
  - Train Precision: 0.9181
  - Train Recall: 0.9322
  - Train F1: 0.9251
  - Train Accuracy: 0.9823
  - Epoch: 2
  
  ## 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': 2631, '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: float32
  
  ### Training results
  
  | Train Loss | Validation Loss | Train Precision | Train Recall | Train F1 | Train Accuracy | Epoch |
  |:----------:|:---------------:|:---------------:|:------------:|:--------:|:--------------:|:-----:|
  | 0.2048     | 0.0749          | 0.8898          | 0.9129       | 0.9012   | 0.9784         | 0     |
  | 0.0556     | 0.0621          | 0.9150          | 0.9300       | 0.9224   | 0.9819         | 1     |
  | 0.0344     | 0.0633          | 0.9181          | 0.9322       | 0.9251   | 0.9823         | 2     |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - TensorFlow 2.8.2
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  