readme: ---
  language:
  - en
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - glue
  metrics:
  - accuracy
  model-index:
  - name: mobilebert_add_GLUE_Experiment_rte
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: GLUE RTE
        type: glue
        config: rte
        split: validation
        args: rte
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.5270758122743683
  ---
  
  <!-- 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_rte
  
  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: 0.6927
  - Accuracy: 0.5271
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 0.6943        | 1.0   | 20   | 0.6933          | 0.4765   |
  | 0.6944        | 2.0   | 40   | 0.6927          | 0.5271   |
  | 0.6932        | 3.0   | 60   | 0.6929          | 0.5271   |
  | 0.6931        | 4.0   | 80   | 0.6951          | 0.4729   |
  | 0.6932        | 5.0   | 100  | 0.6950          | 0.4729   |
  | 0.6918        | 6.0   | 120  | 0.6945          | 0.4440   |
  | 0.6889        | 7.0   | 140  | 0.7189          | 0.4621   |
  
  
  ### Framework versions
  
  - Transformers 4.26.0
  - Pytorch 1.14.0a0+410ce96
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  