readme: ---
  tags:
  - generated_from_keras_callback
  model-index:
  - name: silviacamplani/distilbert-finetuned-dapt_tapt-ner-ai
    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. -->
  
  # silviacamplani/distilbert-finetuned-dapt_tapt-ner-ai
  
  This model was trained from scratch on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Train Loss: 0.8595
  - Validation Loss: 0.8604
  - Train Precision: 0.3378
  - Train Recall: 0.3833
  - Train F1: 0.3591
  - Train Accuracy: 0.7860
  - Epoch: 9
  
  ## 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: {'inner_optimizer': {'class_name': 'AdamWeightDecay', 'config': {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 1e-05, 'decay_steps': 350, '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}}, 'dynamic': True, 'initial_scale': 32768.0, 'dynamic_growth_steps': 2000}
  - training_precision: mixed_float16
  
  ### Training results
  
  | Train Loss | Validation Loss | Train Precision | Train Recall | Train F1 | Train Accuracy | Epoch |
  |:----------:|:---------------:|:---------------:|:------------:|:--------:|:--------------:|:-----:|
  | 2.5333     | 1.7392          | 0.0             | 0.0          | 0.0      | 0.6480         | 0     |
  | 1.5890     | 1.4135          | 0.0             | 0.0          | 0.0      | 0.6480         | 1     |
  | 1.3635     | 1.2627          | 0.0             | 0.0          | 0.0      | 0.6483         | 2     |
  | 1.2366     | 1.1526          | 0.1538          | 0.0920       | 0.1151   | 0.6921         | 3     |
  | 1.1296     | 1.0519          | 0.2147          | 0.2147       | 0.2147   | 0.7321         | 4     |
  | 1.0374     | 0.9753          | 0.2743          | 0.2981       | 0.2857   | 0.7621         | 5     |
  | 0.9639     | 0.9202          | 0.3023          | 0.3373       | 0.3188   | 0.7693         | 6     |
  | 0.9097     | 0.8829          | 0.3215          | 0.3714       | 0.3447   | 0.7795         | 7     |
  | 0.8756     | 0.8635          | 0.3280          | 0.3850       | 0.3542   | 0.7841         | 8     |
  | 0.8595     | 0.8604          | 0.3378          | 0.3833       | 0.3591   | 0.7860         | 9     |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - TensorFlow 2.6.4
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  