readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - quora
  metrics:
  - accuracy
  - f1
  model-index:
  - name: all-MiniLM-L6-v2-quora
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: quora
        type: quora
        config: default
        split: train
        args: default
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.8150291876916989
      - name: F1
        type: f1
        value: 0.794526570313788
  ---
  
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
  should probably proofread and complete it, then remove this comment. -->
  
  # all-MiniLM-L6-v2-quora
  
  This model is a fine-tuned version of [sentence-transformers/all-MiniLM-L6-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2) on the quora dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0865
  - Accuracy: 0.8150
  - F1: 0.7945
  
  ## 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:
  - learning_rate: 5e-05
  - train_batch_size: 32
  - eval_batch_size: 64
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 20
  
  ### Training results
  
  | Training Loss | Epoch | Step   | Validation Loss | Accuracy | F1     |
  |:-------------:|:-----:|:------:|:---------------:|:--------:|:------:|
  | 0.087         | 1.0   | 11371  | 0.0829          | 0.4143   | 0.5535 |
  | 0.0794        | 2.0   | 22742  | 0.0783          | 0.6017   | 0.6458 |
  | 0.0606        | 3.0   | 34113  | 0.0756          | 0.3631   | 0.5327 |
  | 0.05          | 4.0   | 45484  | 0.0781          | 0.4475   | 0.5679 |
  | 0.0448        | 5.0   | 56855  | 0.0789          | 0.6856   | 0.6975 |
  | 0.0372        | 6.0   | 68226  | 0.0761          | 0.3922   | 0.5443 |
  | 0.033         | 7.0   | 79597  | 0.0786          | 0.7586   | 0.7494 |
  | 0.032         | 8.0   | 90968  | 0.0780          | 0.5011   | 0.5927 |
  | 0.0229        | 9.0   | 102339 | 0.0819          | 0.7513   | 0.7439 |
  | 0.0198        | 10.0  | 113710 | 0.0840          | 0.5522   | 0.6185 |
  | 0.0169        | 11.0  | 125081 | 0.0821          | 0.7959   | 0.7785 |
  | 0.0199        | 12.0  | 136452 | 0.0807          | 0.8353   | 0.8118 |
  | 0.0118        | 13.0  | 147823 | 0.0819          | 0.8418   | 0.8176 |
  | 0.0123        | 14.0  | 159194 | 0.0816          | 0.7577   | 0.7487 |
  | 0.0093        | 15.0  | 170565 | 0.0856          | 0.7934   | 0.7765 |
  | 0.0124        | 16.0  | 181936 | 0.0843          | 0.8484   | 0.8241 |
  | 0.008         | 17.0  | 193307 | 0.0838          | 0.7998   | 0.7818 |
  | 0.0106        | 18.0  | 204678 | 0.0872          | 0.8245   | 0.8027 |
  | 0.0066        | 19.0  | 216049 | 0.0857          | 0.8122   | 0.7922 |
  | 0.0059        | 20.0  | 227420 | 0.0865          | 0.8150   | 0.7945 |
  
  
  ### Framework versions
  
  - Transformers 4.21.3
  - Pytorch 1.12.1+cu116
  - Datasets 2.5.1
  - Tokenizers 0.12.1
  