readme: ---
  language:
  - en
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - glue
  metrics:
  - accuracy
  - f1
  model-index:
  - name: distilbert_sa_GLUE_Experiment_data_aug_mrpc_384
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: GLUE MRPC
        type: glue
        args: mrpc
      metrics:
      - name: Accuracy
        type: accuracy
        value: 1.0
      - name: F1
        type: f1
        value: 1.0
  ---
  
  <!-- 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. -->
  
  # distilbert_sa_GLUE_Experiment_data_aug_mrpc_384
  
  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: 0.0000
  - Accuracy: 1.0
  - F1: 1.0
  - Combined Score: 1.0
  
  ## 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: 256
  - eval_batch_size: 256
  - 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
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1  | Combined Score |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:---:|:--------------:|
  | 0.1771        | 1.0   | 980   | 0.0049          | 1.0      | 1.0 | 1.0            |
  | 0.0321        | 2.0   | 1960  | 0.0009          | 1.0      | 1.0 | 1.0            |
  | 0.0154        | 3.0   | 2940  | 0.0001          | 1.0      | 1.0 | 1.0            |
  | 0.0086        | 4.0   | 3920  | 0.0009          | 1.0      | 1.0 | 1.0            |
  | 0.0062        | 5.0   | 4900  | 0.0000          | 1.0      | 1.0 | 1.0            |
  | 0.0039        | 6.0   | 5880  | 0.0000          | 1.0      | 1.0 | 1.0            |
  | 0.0039        | 7.0   | 6860  | 0.0000          | 1.0      | 1.0 | 1.0            |
  | 0.0028        | 8.0   | 7840  | 0.0000          | 1.0      | 1.0 | 1.0            |
  | 0.0022        | 9.0   | 8820  | 0.0000          | 1.0      | 1.0 | 1.0            |
  | 0.0018        | 10.0  | 9800  | 0.0000          | 1.0      | 1.0 | 1.0            |
  | 0.002         | 11.0  | 10780 | 0.0000          | 1.0      | 1.0 | 1.0            |
  | 0.0011        | 12.0  | 11760 | 0.0000          | 1.0      | 1.0 | 1.0            |
  | 0.0015        | 13.0  | 12740 | 0.0000          | 1.0      | 1.0 | 1.0            |
  | 0.0011        | 14.0  | 13720 | 0.0000          | 1.0      | 1.0 | 1.0            |
  | 0.0011        | 15.0  | 14700 | 0.0000          | 1.0      | 1.0 | 1.0            |
  | 0.0008        | 16.0  | 15680 | 0.0000          | 1.0      | 1.0 | 1.0            |
  | 0.0009        | 17.0  | 16660 | 0.0000          | 1.0      | 1.0 | 1.0            |
  | 0.0007        | 18.0  | 17640 | 0.0001          | 1.0      | 1.0 | 1.0            |
  | 0.0006        | 19.0  | 18620 | 0.0000          | 1.0      | 1.0 | 1.0            |
  | 0.0006        | 20.0  | 19600 | 0.0000          | 1.0      | 1.0 | 1.0            |
  | 0.0004        | 21.0  | 20580 | 0.0000          | 1.0      | 1.0 | 1.0            |
  | 0.0004        | 22.0  | 21560 | 0.0000          | 1.0      | 1.0 | 1.0            |
  | 0.0002        | 23.0  | 22540 | 0.0000          | 1.0      | 1.0 | 1.0            |
  | 0.0004        | 24.0  | 23520 | 0.0000          | 1.0      | 1.0 | 1.0            |
  | 0.0003        | 25.0  | 24500 | 0.0000          | 1.0      | 1.0 | 1.0            |
  | 0.0004        | 26.0  | 25480 | 0.0000          | 1.0      | 1.0 | 1.0            |
  | 0.0003        | 27.0  | 26460 | 0.0000          | 1.0      | 1.0 | 1.0            |
  | 0.0002        | 28.0  | 27440 | 0.0000          | 1.0      | 1.0 | 1.0            |
  | 0.0002        | 29.0  | 28420 | 0.0000          | 1.0      | 1.0 | 1.0            |
  
  
  ### Framework versions
  
  - Transformers 4.26.0
  - Pytorch 1.14.0a0+410ce96
  - Datasets 2.9.0
  - Tokenizers 0.13.2
  