readme: ---
  license: apache-2.0
  tags:
  - generated_from_keras_callback
  model-index:
  - name: kasrahabib/kasrahabib-finetunned-90percentile-384embd-kmeans-propogated
    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/kasrahabib-finetunned-90percentile-384embd-kmeans-propogated
  
  This model is a fine-tuned version of [kasrahabib/all-MiniLM-L6-v2-finetunned-fnfreq-clf-promise-finetunned-fnfreq-clf-promise-third](https://huggingface.co/kasrahabib/all-MiniLM-L6-v2-finetunned-fnfreq-clf-promise-finetunned-fnfreq-clf-promise-third) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Train Loss: 0.0174
  - Validation Loss: 0.0847
  - Train Precision: 0.9737
  - Train Recall: 0.9879
  - Train F1: 0.9808
  - 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': 2070, '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 |
  |:----------:|:---------------:|:---------------:|:------------:|:--------:|:-----:|
  | 0.0971     | 0.0656          | 0.9647          | 0.9927       | 0.9785   | 0     |
  | 0.0569     | 0.0634          | 0.9737          | 0.9879       | 0.9808   | 1     |
  | 0.0316     | 0.0752          | 0.9737          | 0.9879       | 0.9808   | 2     |
  | 0.0177     | 0.0793          | 0.9737          | 0.9855       | 0.9795   | 3     |
  | 0.0174     | 0.0847          | 0.9737          | 0.9879       | 0.9808   | 4     |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - TensorFlow 2.9.2
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  