readme: ---
  license: apache-2.0
  tags:
  - generated_from_keras_callback
  model-index:
  - name: silviacamplani/distilbert-finetuned-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-ner-ai
  
  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: 0.8962
  - Validation Loss: 0.9088
  - Train Precision: 0.3895
  - Train Recall: 0.3901
  - Train F1: 0.3898
  - Train Accuracy: 0.7558
  - 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 |
  |:----------:|:---------------:|:---------------:|:------------:|:--------:|:--------------:|:-----:|
  | 2.5761     | 1.7934          | 0.0             | 0.0          | 0.0      | 0.6480         | 0     |
  | 1.7098     | 1.5860          | 0.0             | 0.0          | 0.0      | 0.6480         | 1     |
  | 1.4692     | 1.3213          | 0.0             | 0.0          | 0.0      | 0.6480         | 2     |
  | 1.2755     | 1.1859          | 0.1154          | 0.0460       | 0.0658   | 0.6789         | 3     |
  | 1.1561     | 1.0921          | 0.2878          | 0.2010       | 0.2367   | 0.7192         | 4     |
  | 1.0652     | 1.0170          | 0.3250          | 0.2862       | 0.3043   | 0.7354         | 5     |
  | 0.9936     | 0.9649          | 0.3489          | 0.3305       | 0.3395   | 0.7462         | 6     |
  | 0.9442     | 0.9340          | 0.3845          | 0.3799       | 0.3822   | 0.7549         | 7     |
  | 0.9097     | 0.9168          | 0.3866          | 0.3748       | 0.3806   | 0.7556         | 8     |
  | 0.8962     | 0.9088          | 0.3895          | 0.3901       | 0.3898   | 0.7558         | 9     |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - TensorFlow 2.6.4
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  