readme: ---
  language:
  - en
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - glue
  metrics:
  - accuracy
  model-index:
  - name: mobilebert_add_GLUE_Experiment_sst2
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: GLUE SST2
        type: glue
        config: sst2
        split: validation
        args: sst2
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.7970183486238532
  ---
  
  <!-- 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_add_GLUE_Experiment_sst2
  
  This model is a fine-tuned version of [google/mobilebert-uncased](https://huggingface.co/google/mobilebert-uncased) on the GLUE SST2 dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4671
  - Accuracy: 0.7970
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 0.6635        | 1.0   | 527  | 0.6994          | 0.5390   |
  | 0.5959        | 2.0   | 1054 | 0.6921          | 0.5665   |
  | 0.5684        | 3.0   | 1581 | 0.7082          | 0.5516   |
  | 0.5544        | 4.0   | 2108 | 0.6883          | 0.5619   |
  | 0.5471        | 5.0   | 2635 | 0.6938          | 0.5940   |
  | 0.5414        | 6.0   | 3162 | 0.7045          | 0.5803   |
  | 0.5381        | 7.0   | 3689 | 0.7354          | 0.5654   |
  | 0.5338        | 8.0   | 4216 | 0.7316          | 0.5826   |
  | 0.3529        | 9.0   | 4743 | 0.4671          | 0.7970   |
  | 0.2415        | 10.0  | 5270 | 0.4722          | 0.7982   |
  | 0.2075        | 11.0  | 5797 | 0.4797          | 0.8062   |
  | 0.1862        | 12.0  | 6324 | 0.5134          | 0.7993   |
  | 0.1724        | 13.0  | 6851 | 0.5256          | 0.7993   |
  | 0.1662        | 14.0  | 7378 | 0.5706          | 0.8028   |
  
  
  ### Framework versions
  
  - Transformers 4.26.0
  - Pytorch 1.14.0a0+410ce96
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  