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_256
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: GLUE MRPC
        type: glue
        args: mrpc
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.9926470588235294
      - name: F1
        type: f1
        value: 0.9946524064171123
  ---
  
  <!-- 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_256
  
  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: 0.1267
  - Accuracy: 0.9926
  - F1: 0.9947
  - Combined Score: 0.9936
  
  ## 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 |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:|
  | 0.3017        | 1.0   | 1959  | 0.2241          | 0.9608   | 0.9713 | 0.9661         |
  | 0.233         | 2.0   | 3918  | 0.2357          | 0.9828   | 0.9876 | 0.9852         |
  | 0.2241        | 3.0   | 5877  | 0.1908          | 0.9706   | 0.9786 | 0.9746         |
  | 0.2189        | 4.0   | 7836  | 0.1863          | 0.9755   | 0.9824 | 0.9789         |
  | 0.2149        | 5.0   | 9795  | 0.1868          | 0.9804   | 0.9858 | 0.9831         |
  | 0.211         | 6.0   | 11754 | 0.1735          | 0.9804   | 0.9859 | 0.9831         |
  | 0.2073        | 7.0   | 13713 | 0.1875          | 0.9828   | 0.9876 | 0.9852         |
  | 0.204         | 8.0   | 15672 | 0.1690          | 0.9853   | 0.9894 | 0.9873         |
  | 0.2014        | 9.0   | 17631 | 0.1597          | 0.9853   | 0.9893 | 0.9873         |
  | 0.1992        | 10.0  | 19590 | 0.1604          | 0.9877   | 0.9911 | 0.9894         |
  | 0.1975        | 11.0  | 21549 | 0.1563          | 0.9853   | 0.9894 | 0.9873         |
  | 0.1959        | 12.0  | 23508 | 0.1518          | 0.9853   | 0.9894 | 0.9873         |
  | 0.1948        | 13.0  | 25467 | 0.1429          | 0.9902   | 0.9929 | 0.9915         |
  | 0.1937        | 14.0  | 27426 | 0.1484          | 0.9853   | 0.9894 | 0.9873         |
  | 0.1928        | 15.0  | 29385 | 0.1527          | 0.9804   | 0.9856 | 0.9830         |
  | 0.1919        | 16.0  | 31344 | 0.1433          | 0.9926   | 0.9947 | 0.9936         |
  | 0.1913        | 17.0  | 33303 | 0.1445          | 0.9902   | 0.9929 | 0.9915         |
  | 0.1905        | 18.0  | 35262 | 0.1407          | 0.9926   | 0.9947 | 0.9936         |
  | 0.1899        | 19.0  | 37221 | 0.1402          | 0.9926   | 0.9947 | 0.9936         |
  | 0.1892        | 20.0  | 39180 | 0.1387          | 0.9926   | 0.9947 | 0.9936         |
  | 0.1887        | 21.0  | 41139 | 0.1384          | 0.9926   | 0.9947 | 0.9936         |
  | 0.1882        | 22.0  | 43098 | 0.1430          | 0.9951   | 0.9964 | 0.9958         |
  | 0.1877        | 23.0  | 45057 | 0.1384          | 0.9951   | 0.9964 | 0.9958         |
  | 0.1871        | 24.0  | 47016 | 0.1398          | 0.9951   | 0.9964 | 0.9958         |
  | 0.1867        | 25.0  | 48975 | 0.1336          | 0.9926   | 0.9947 | 0.9936         |
  | 0.1863        | 26.0  | 50934 | 0.1368          | 0.9951   | 0.9964 | 0.9958         |
  | 0.1859        | 27.0  | 52893 | 0.1337          | 0.9951   | 0.9964 | 0.9958         |
  | 0.1855        | 28.0  | 54852 | 0.1352          | 0.9926   | 0.9947 | 0.9936         |
  | 0.1851        | 29.0  | 56811 | 0.1314          | 0.9951   | 0.9964 | 0.9958         |
  | 0.1847        | 30.0  | 58770 | 0.1333          | 0.9951   | 0.9964 | 0.9958         |
  | 0.1844        | 31.0  | 60729 | 0.1368          | 0.9951   | 0.9964 | 0.9958         |
  | 0.184         | 32.0  | 62688 | 0.1310          | 0.9951   | 0.9964 | 0.9958         |
  | 0.1837        | 33.0  | 64647 | 0.1321          | 0.9951   | 0.9964 | 0.9958         |
  | 0.1834        | 34.0  | 66606 | 0.1302          | 0.9926   | 0.9947 | 0.9936         |
  | 0.183         | 35.0  | 68565 | 0.1320          | 0.9951   | 0.9964 | 0.9958         |
  | 0.1827        | 36.0  | 70524 | 0.1303          | 0.9951   | 0.9964 | 0.9958         |
  | 0.1825        | 37.0  | 72483 | 0.1273          | 0.9951   | 0.9964 | 0.9958         |
  |