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_data_aug_mrpc
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: GLUE MRPC
        type: glue
        args: mrpc
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.9877450980392157
      - name: F1
        type: f1
        value: 0.9911190053285969
  ---
  
  <!-- 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_data_aug_mrpc
  
  This model is a fine-tuned version of [google/mobilebert-uncased](https://huggingface.co/google/mobilebert-uncased) on the GLUE MRPC dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1256
  - Accuracy: 0.9877
  - F1: 0.9911
  - Combined Score: 0.9894
  
  ## 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 |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:|
  | 0.2964        | 1.0   | 1959  | 0.2026          | 0.9608   | 0.9718 | 0.9663         |
  | 0.2307        | 2.0   | 3918  | 0.1943          | 0.9706   | 0.9789 | 0.9748         |
  | 0.2221        | 3.0   | 5877  | 0.1874          | 0.9804   | 0.9858 | 0.9831         |
  | 0.2163        | 4.0   | 7836  | 0.1703          | 0.9853   | 0.9894 | 0.9873         |
  | 0.2115        | 5.0   | 9795  | 0.1805          | 0.9853   | 0.9894 | 0.9873         |
  | 0.2071        | 6.0   | 11754 | 0.1682          | 0.9804   | 0.9859 | 0.9831         |
  | 0.2036        | 7.0   | 13713 | 0.1583          | 0.9877   | 0.9911 | 0.9894         |
  | 0.2007        | 8.0   | 15672 | 0.1628          | 0.9926   | 0.9947 | 0.9936         |
  | 0.1985        | 9.0   | 17631 | 0.1548          | 0.9853   | 0.9894 | 0.9873         |
  | 0.1965        | 10.0  | 19590 | 0.1583          | 0.9877   | 0.9911 | 0.9894         |
  | 0.195         | 11.0  | 21549 | 0.1527          | 0.9902   | 0.9928 | 0.9915         |
  | 0.1938        | 12.0  | 23508 | 0.1512          | 0.9902   | 0.9929 | 0.9915         |
  | 0.1926        | 13.0  | 25467 | 0.1426          | 0.9951   | 0.9964 | 0.9958         |
  | 0.1917        | 14.0  | 27426 | 0.1436          | 0.9951   | 0.9964 | 0.9958         |
  | 0.191         | 15.0  | 29385 | 0.1503          | 0.9926   | 0.9946 | 0.9936         |
  | 0.1901        | 16.0  | 31344 | 0.1461          | 0.9951   | 0.9964 | 0.9958         |
  | 0.1894        | 17.0  | 33303 | 0.1498          | 0.9975   | 0.9982 | 0.9979         |
  | 0.1888        | 18.0  | 35262 | 0.1402          | 0.9902   | 0.9929 | 0.9915         |
  | 0.1882        | 19.0  | 37221 | 0.1420          | 0.9926   | 0.9946 | 0.9936         |
  | 0.1876        | 20.0  | 39180 | 0.1346          | 0.9902   | 0.9929 | 0.9915         |
  | 0.1871        | 21.0  | 41139 | 0.1396          | 0.9951   | 0.9964 | 0.9958         |
  | 0.1867        | 22.0  | 43098 | 0.1443          | 0.9951   | 0.9964 | 0.9958         |
  | 0.1862        | 23.0  | 45057 | 0.1346          | 0.9926   | 0.9947 | 0.9936         |
  | 0.1857        | 24.0  | 47016 | 0.1361          | 0.9951   | 0.9964 | 0.9958         |
  | 0.1854        | 25.0  | 48975 | 0.1318          | 0.9926   | 0.9947 | 0.9936         |
  | 0.185         | 26.0  | 50934 | 0.1310          | 0.9902   | 0.9929 | 0.9915         |
  | 0.1846        | 27.0  | 52893 | 0.1302          | 0.9926   | 0.9947 | 0.9936         |
  | 0.1842        | 28.0  | 54852 | 0.1329          | 0.9951   | 0.9964 | 0.9958         |
  | 0.1839        | 29.0  | 56811 | 0.1300          | 0.9902   | 0.9929 | 0.9915         |
  | 0.1836        | 30.0  | 58770 | 0.1328          | 0.9902   | 0.9929 | 0.9915         |
  | 0.1832        | 31.0  | 60729 | 0.1327          | 0.9902   | 0.9929 | 0.9915         |
  | 0.1829        | 32.0  | 62688 | 0.1308          | 0.9902   | 0.9929 | 0.9915         |
  | 0.1826        | 33.0  | 64647 | 0.1287          | 0.9902   | 0.9929 | 0.9915         |
  | 0.1824        | 34.0  | 66606 | 0.1309          | 0.9926   | 0.9947 | 0.9936         |
  | 0.1821        | 35.0  | 68565 | 0.1309          | 0.9926   | 0.9947 | 0.9936         |
  | 0.1818        | 36.0  | 70524 | 0.1271          | 0.9902   | 0.9929 | 0.9915         |
  | 0.1816        | 37.0  | 72483 | 0.1278          | 0.9877   | 0.9911 | 0.9894         |
  | 0.1813 