readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: tiny-mlm-glue-cola-target-glue-mnli
    results: []
  ---
  
  <!-- 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. -->
  
  # tiny-mlm-glue-cola-target-glue-mnli
  
  This model is a fine-tuned version of [muhtasham/tiny-mlm-glue-cola](https://huggingface.co/muhtasham/tiny-mlm-glue-cola) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.8037
  - Accuracy: 0.6427
  
  ## 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: 3e-05
  - train_batch_size: 32
  - eval_batch_size: 32
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: constant
  - num_epochs: 200
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Accuracy |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
  | 1.0736        | 0.04  | 500   | 1.0266          | 0.4807   |
  | 1.0005        | 0.08  | 1000  | 0.9516          | 0.5605   |
  | 0.9517        | 0.12  | 1500  | 0.9140          | 0.5810   |
  | 0.9271        | 0.16  | 2000  | 0.9009          | 0.5921   |
  | 0.919         | 0.2   | 2500  | 0.8858          | 0.6014   |
  | 0.9125        | 0.24  | 3000  | 0.8740          | 0.6069   |
  | 0.8965        | 0.29  | 3500  | 0.8676          | 0.6134   |
  | 0.89          | 0.33  | 4000  | 0.8547          | 0.6193   |
  | 0.8754        | 0.37  | 4500  | 0.8516          | 0.6214   |
  | 0.8779        | 0.41  | 5000  | 0.8448          | 0.6220   |
  | 0.8698        | 0.45  | 5500  | 0.8396          | 0.6252   |
  | 0.8653        | 0.49  | 6000  | 0.8371          | 0.6287   |
  | 0.8692        | 0.53  | 6500  | 0.8304          | 0.6309   |
  | 0.8579        | 0.57  | 7000  | 0.8307          | 0.6301   |
  | 0.8528        | 0.61  | 7500  | 0.8151          | 0.6409   |
  | 0.8538        | 0.65  | 8000  | 0.8153          | 0.6381   |
  | 0.8451        | 0.69  | 8500  | 0.8264          | 0.6329   |
  | 0.8497        | 0.73  | 9000  | 0.8002          | 0.6464   |
  | 0.8401        | 0.77  | 9500  | 0.8125          | 0.6363   |
  | 0.8299        | 0.81  | 10000 | 0.7968          | 0.6464   |
  | 0.8343        | 0.86  | 10500 | 0.8037          | 0.6427   |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  