readme: ---
  language:
  - en
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - glue
  metrics:
  - accuracy
  model-index:
  - name: mobilebert_sa_GLUE_Experiment_mnli
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: GLUE MNLI
        type: glue
        config: mnli
        split: validation_matched
        args: mnli
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.6110659072416599
  ---
  
  <!-- 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_mnli
  
  This model is a fine-tuned version of [google/mobilebert-uncased](https://huggingface.co/google/mobilebert-uncased) on the GLUE MNLI dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.8609
  - Accuracy: 0.6111
  
  ## 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
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Accuracy |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
  | 0.9907        | 1.0   | 3068  | 0.9408          | 0.5485   |
  | 0.9094        | 2.0   | 6136  | 0.9065          | 0.5819   |
  | 0.8828        | 3.0   | 9204  | 0.8969          | 0.5874   |
  | 0.8627        | 4.0   | 12272 | 0.8821          | 0.5967   |
  | 0.8429        | 5.0   | 15340 | 0.8743          | 0.6003   |
  | 0.8207        | 6.0   | 18408 | 0.8663          | 0.6077   |
  | 0.7989        | 7.0   | 21476 | 0.8665          | 0.6100   |
  | 0.7789        | 8.0   | 24544 | 0.8751          | 0.6096   |
  | 0.7603        | 9.0   | 27612 | 0.8620          | 0.6139   |
  | 0.7425        | 10.0  | 30680 | 0.8813          | 0.6095   |
  | 0.7238        | 11.0  | 33748 | 0.8913          | 0.6142   |
  | 0.7063        | 12.0  | 36816 | 0.9026          | 0.6056   |
  | 0.6891        | 13.0  | 39884 | 0.9267          | 0.5976   |
  | 0.6721        | 14.0  | 42952 | 0.9072          | 0.6105   |
  
  
  ### Framework versions
  
  - Transformers 4.26.0
  - Pytorch 1.14.0a0+410ce96
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  