readme: ---
  language:
  - en
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - glue
  metrics:
  - accuracy
  model-index:
  - name: mobilebert_sa_GLUE_Experiment_data_aug_rte_256
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: GLUE RTE
        type: glue
        args: rte
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.48736462093862815
  ---
  
  <!-- 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_data_aug_rte_256
  
  This model is a fine-tuned version of [google/mobilebert-uncased](https://huggingface.co/google/mobilebert-uncased) on the GLUE RTE dataset.
  It achieves the following results on the evaluation set:
  - Loss: 3.0847
  - Accuracy: 0.4874
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 0.2703        | 1.0   | 1136 | 3.2768          | 0.4657   |
  | 0.0555        | 2.0   | 2272 | 3.0847          | 0.4874   |
  | 0.0253        | 3.0   | 3408 | 5.4968          | 0.5018   |
  | 0.0149        | 4.0   | 4544 | 5.6020          | 0.4982   |
  | 0.0104        | 5.0   | 5680 | 6.6683          | 0.5090   |
  | 0.0082        | 6.0   | 6816 | 8.2220          | 0.5090   |
  | 0.0062        | 7.0   | 7952 | 8.2179          | 0.5054   |
  
  
  ### Framework versions
  
  - Transformers 4.26.0
  - Pytorch 1.14.0a0+410ce96
  - Datasets 2.9.0
  - Tokenizers 0.13.2
  