readme: ---
  language:
  - en
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - glue
  metrics:
  - accuracy
  - f1
  model-index:
  - name: Glue_distilbert
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: GLUE MRPC
        type: glue
        args: mrpc
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.8504901960784313
      - name: F1
        type: f1
        value: 0.8960817717206134
  ---
  
  <!-- 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. -->
  
  # Glue_distilbert
  
  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the GLUE MRPC dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.1042
  - Accuracy: 0.8505
  - F1: 0.8961
  - Combined Score: 0.8733
  
  ## 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: 32
  - seed: 33
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 50
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Combined Score |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
  | 0.5066        | 1.0   | 115  | 0.3833          | 0.8358   | 0.8851 | 0.8604         |
  | 0.3227        | 2.0   | 230  | 0.4336          | 0.8309   | 0.8844 | 0.8577         |
  | 0.1764        | 3.0   | 345  | 0.4943          | 0.8309   | 0.8757 | 0.8533         |
  | 0.0792        | 4.0   | 460  | 0.7271          | 0.8431   | 0.8861 | 0.8646         |
  | 0.058         | 5.0   | 575  | 0.8374          | 0.8456   | 0.8945 | 0.8700         |
  | 0.0594        | 6.0   | 690  | 0.7570          | 0.8309   | 0.8816 | 0.8563         |
  | 0.0395        | 7.0   | 805  | 0.8640          | 0.8431   | 0.8897 | 0.8664         |
  | 0.03          | 8.0   | 920  | 0.9007          | 0.8260   | 0.8799 | 0.8529         |
  | 0.0283        | 9.0   | 1035 | 0.9479          | 0.8211   | 0.8685 | 0.8448         |
  | 0.0127        | 10.0  | 1150 | 1.0686          | 0.8431   | 0.8915 | 0.8673         |
  | 0.0097        | 11.0  | 1265 | 1.0752          | 0.8431   | 0.8919 | 0.8675         |
  | 0.0164        | 12.0  | 1380 | 1.0627          | 0.8284   | 0.8801 | 0.8543         |
  | 0.007         | 13.0  | 1495 | 1.1466          | 0.8333   | 0.8815 | 0.8574         |
  | 0.0132        | 14.0  | 1610 | 1.1442          | 0.8456   | 0.8938 | 0.8697         |
  | 0.0125        | 15.0  | 1725 | 1.1716          | 0.8235   | 0.8771 | 0.8503         |
  | 0.0174        | 16.0  | 1840 | 1.1187          | 0.8333   | 0.8790 | 0.8562         |
  | 0.0171        | 17.0  | 1955 | 1.1053          | 0.8456   | 0.8938 | 0.8697         |
  | 0.0026        | 18.0  | 2070 | 1.2011          | 0.8309   | 0.8787 | 0.8548         |
  | 0.0056        | 19.0  | 2185 | 1.3085          | 0.8260   | 0.8748 | 0.8504         |
  | 0.0067        | 20.0  | 2300 | 1.3042          | 0.8333   | 0.8803 | 0.8568         |
  | 0.0129        | 21.0  | 2415 | 1.1042          | 0.8505   | 0.8961 | 0.8733         |
  | 0.0149        | 22.0  | 2530 | 1.1575          | 0.8235   | 0.8820 | 0.8527         |
  | 0.0045        | 23.0  | 2645 | 1.2359          | 0.8407   | 0.8900 | 0.8654         |
  | 0.0029        | 24.0  | 2760 | 1.3823          | 0.8211   | 0.8744 | 0.8477         |
  | 0.0074        | 25.0  | 2875 | 1.2394          | 0.8431   | 0.8904 | 0.8668         |
  | 0.002         | 26.0  | 2990 | 1.4450          | 0.8333   | 0.8859 | 0.8596         |
  | 0.0039        | 27.0  | 3105 | 1.5102          | 0.8284   | 0.8805 | 0.8545         |
  | 0.0015        | 28.0  | 3220 | 1.4767          | 0.8431   | 0.8915 | 0.8673         |
  | 0.0062        | 29.0  | 3335 | 1.5101          | 0.8407   | 0.8926 | 0.8666         |
  | 0.0054        | 30.0  | 3450 | 1.3861          | 0.8382   | 0.8893 | 0.8637         |
  | 0.0001        | 31.0  | 3565 | 1.4101          | 0.8456   | 0.8948 | 0.8702         |
  | 0.0           | 32.0  | 3680 | 1.4203          | 0.8480   | 0.8963 | 0.8722         |
  | 0.002         | 33.0  | 3795 | 1.4526          | 0.8431   | 0.8923 | 0.8677         |
  | 0.0019        | 34.0  | 3910 | 1.6265          | 0.8260   | 0.8842 | 0.8551         |
  | 0.0029        | 35.0  | 4025 | 1.4788          | 0.8456   | 0.8945 | 0.8700         |
  | 0.0           | 36.0  | 4140 | 1.4668          | 0.8480   | 0.8956 | 0.8718         |
  | 0.0007        | 37.0  | 4255 | 1.5248          | 0.8456   | 0.8945 | 0.8700         |
  | 0.0           | 38.0  | 4370 | 1.5202          | 0.8480   | 0.8960 | 0.8720         |
  | 0.0033        | 39.0  | 4485 