readme: ---
  license: apache-2.0
  tags:
  - generated_from_keras_callback
  model-index:
  - name: afrodp95/distilbert-base-uncased-finetuned-job-skills-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. -->
  
  # afrodp95/distilbert-base-uncased-finetuned-job-skills-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: 0.0923
  - Validation Loss: 0.1313
  - Train Precision: 0.3601
  - Train Recall: 0.4922
  - Train F1: 0.4159
  - Train Accuracy: 0.9522
  - Epoch: 5
  
  ## 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': 3e-05, 'decay_steps': 1386, '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 |
  |:----------:|:---------------:|:---------------:|:------------:|:--------:|:--------------:|:-----:|
  | 0.3257     | 0.1935          | 0.3122          | 0.2144       | 0.2542   | 0.9521         | 0     |
  | 0.1564     | 0.1464          | 0.3503          | 0.3423       | 0.3463   | 0.9546         | 1     |
  | 0.1257     | 0.1365          | 0.3593          | 0.4893       | 0.4143   | 0.9522         | 2     |
  | 0.1102     | 0.1318          | 0.3607          | 0.4692       | 0.4079   | 0.9521         | 3     |
  | 0.1002     | 0.1305          | 0.3504          | 0.4941       | 0.4100   | 0.9515         | 4     |
  | 0.0923     | 0.1313          | 0.3601          | 0.4922       | 0.4159   | 0.9522         | 5     |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - TensorFlow 2.9.2
  - Datasets 2.6.1
  - Tokenizers 0.13.2
  