readme: ---
  license: apache-2.0
  tags:
  - generated_from_keras_callback
  model-index:
  - name: kasrahabib/all-MiniLM-L6-v2-finetunned-fnfreq-clf-promise-finetunned-fnfreq-clf-promise_second
    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. -->
  
  # kasrahabib/all-MiniLM-L6-v2-finetunned-fnfreq-clf-promise-finetunned-fnfreq-clf-promise_second
  
  This model is a fine-tuned version of [kasrahabib/all-MiniLM-L6-v2-finetunned-fnfreq-clf-promise](https://huggingface.co/kasrahabib/all-MiniLM-L6-v2-finetunned-fnfreq-clf-promise) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Train Loss: 0.0598
  - Validation Loss: 0.1193
  - Train Precision: 0.9867
  - Train Recall: 1.0
  - Train F1: 0.9933
  - Epoch: 4
  
  ## 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': 'Adam', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 310, '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}
  - training_precision: float32
  
  ### Training results
  
  | Train Loss | Validation Loss | Train Precision | Train Recall | Train F1 | Epoch |
  |:----------:|:---------------:|:---------------:|:------------:|:--------:|:-----:|
  | 0.1967     | 0.1568          | 0.9733          | 0.9865       | 0.9799   | 0     |
  | 0.1451     | 0.1347          | 0.9865          | 0.9865       | 0.9865   | 1     |
  | 0.0990     | 0.1243          | 0.9733          | 0.9865       | 0.9799   | 2     |
  | 0.0785     | 0.1227          | 0.9733          | 0.9865       | 0.9799   | 3     |
  | 0.0598     | 0.1193          | 0.9867          | 1.0          | 0.9933   | 4     |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - TensorFlow 2.9.0
  - Datasets 2.7.1
  - Tokenizers 0.13.1
  