readme: ---
  language:
  - en
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - glue
  metrics:
  - accuracy
  - f1
  model-index:
  - name: mobilebert_sa_GLUE_Experiment_logit_kd_pretrain_qqp
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: GLUE QQP
        type: glue
        config: qqp
        split: validation
        args: qqp
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.9133069502844422
      - name: F1
        type: f1
        value: 0.8843348843348843
  ---
  
  <!-- 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. -->
  
  # mobilebert_sa_GLUE_Experiment_logit_kd_pretrain_qqp
  
  This model is a fine-tuned version of [gokuls/mobilebert_sa_pre-training-complete](https://huggingface.co/gokuls/mobilebert_sa_pre-training-complete) on the GLUE QQP dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1715
  - Accuracy: 0.9133
  - F1: 0.8843
  - Combined Score: 0.8988
  
  ## 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: 128
  - eval_batch_size: 128
  - seed: 10
  - distributed_type: multi-GPU
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 50
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Combined Score |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:|
  | 0.3902        | 1.0   | 2843  | 0.2870          | 0.8788   | 0.8463 | 0.8625         |
  | 0.226         | 2.0   | 5686  | 0.1968          | 0.8979   | 0.8649 | 0.8814         |
  | 0.1681        | 3.0   | 8529  | 0.1910          | 0.9038   | 0.8719 | 0.8878         |
  | 0.1346        | 4.0   | 11372 | 0.1989          | 0.9055   | 0.8772 | 0.8914         |
  | 0.1124        | 5.0   | 14215 | 0.1970          | 0.9049   | 0.8747 | 0.8898         |
  | 0.0978        | 6.0   | 17058 | 0.1876          | 0.9095   | 0.8806 | 0.8950         |
  | 0.0876        | 7.0   | 19901 | 0.1893          | 0.9077   | 0.8773 | 0.8925         |
  | 0.0802        | 8.0   | 22744 | 0.1940          | 0.9067   | 0.8773 | 0.8920         |
  | 0.0746        | 9.0   | 25587 | 0.1846          | 0.9090   | 0.8787 | 0.8938         |
  | 0.0699        | 10.0  | 28430 | 0.1890          | 0.9093   | 0.8809 | 0.8951         |
  | 0.0663        | 11.0  | 31273 | 0.1803          | 0.9103   | 0.8804 | 0.8953         |
  | 0.0632        | 12.0  | 34116 | 0.1905          | 0.9084   | 0.8805 | 0.8945         |
  | 0.0606        | 13.0  | 36959 | 0.1835          | 0.9094   | 0.8813 | 0.8953         |
  | 0.0583        | 14.0  | 39802 | 0.1786          | 0.9112   | 0.8805 | 0.8958         |
  | 0.0562        | 15.0  | 42645 | 0.1900          | 0.9091   | 0.8817 | 0.8954         |
  | 0.0546        | 16.0  | 45488 | 0.1753          | 0.9126   | 0.8825 | 0.8975         |
  | 0.0529        | 17.0  | 48331 | 0.1761          | 0.9121   | 0.8825 | 0.8973         |
  | 0.0515        | 18.0  | 51174 | 0.1784          | 0.9129   | 0.8842 | 0.8986         |
  | 0.0501        | 19.0  | 54017 | 0.1730          | 0.9129   | 0.8847 | 0.8988         |
  | 0.049         | 20.0  | 56860 | 0.1812          | 0.9116   | 0.8835 | 0.8975         |
  | 0.0479        | 21.0  | 59703 | 0.1751          | 0.9115   | 0.8830 | 0.8972         |
  | 0.0469        | 22.0  | 62546 | 0.1737          | 0.9120   | 0.8833 | 0.8976         |
  | 0.0461        | 23.0  | 65389 | 0.1739          | 0.9129   | 0.8844 | 0.8986         |
  | 0.0452        | 24.0  | 68232 | 0.1715          | 0.9133   | 0.8843 | 0.8988         |
  | 0.0447        | 25.0  | 71075 | 0.1748          | 0.9119   | 0.8844 | 0.8982         |
  | 0.0437        | 26.0  | 73918 | 0.1734          | 0.9129   | 0.8841 | 0.8985         |
  | 0.0431        | 27.0  | 76761 | 0.1727          | 0.9125   | 0.8830 | 0.8977         |
  | 0.0425        | 28.0  | 79604 | 0.1803          | 0.9120   | 0.8851 | 0.8985         |
  | 0.0419        | 29.0  | 82447 | 0.1720          | 0.9124   | 0.8835 | 0.8980         |
  
  
  ### Framework versions
  
  - Transformers 4.26.0
  - Pytorch 1.14.0a0+410ce96
  - Datasets 2.9.0
  - Tokenizers 0.13.2
  