readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: tiny-mlm-glue-qqp-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-qqp-target-glue-mnli
  
  This model is a fine-tuned version of [muhtasham/tiny-mlm-glue-qqp](https://huggingface.co/muhtasham/tiny-mlm-glue-qqp) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.8018
  - Accuracy: 0.6440
  
  ## 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 |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
  | 1.0756        | 0.04  | 500   | 1.0341          | 0.4692   |
  | 1.009         | 0.08  | 1000  | 0.9636          | 0.5497   |
  | 0.9589        | 0.12  | 1500  | 0.9186          | 0.5777   |
  | 0.9309        | 0.16  | 2000  | 0.9050          | 0.5885   |
  | 0.9229        | 0.2   | 2500  | 0.8882          | 0.5992   |
  | 0.9154        | 0.24  | 3000  | 0.8755          | 0.6048   |
  | 0.8993        | 0.29  | 3500  | 0.8683          | 0.6136   |
  | 0.8917        | 0.33  | 4000  | 0.8555          | 0.6193   |
  | 0.8757        | 0.37  | 4500  | 0.8553          | 0.6165   |
  | 0.8796        | 0.41  | 5000  | 0.8441          | 0.6235   |
  | 0.8705        | 0.45  | 5500  | 0.8400          | 0.6239   |
  | 0.8656        | 0.49  | 6000  | 0.8362          | 0.6289   |
  | 0.8692        | 0.53  | 6500  | 0.8298          | 0.6307   |
  | 0.8585        | 0.57  | 7000  | 0.8287          | 0.6315   |
  | 0.8529        | 0.61  | 7500  | 0.8139          | 0.6400   |
  | 0.8534        | 0.65  | 8000  | 0.8133          | 0.6391   |
  | 0.8449        | 0.69  | 8500  | 0.8223          | 0.6342   |
  | 0.8505        | 0.73  | 9000  | 0.7989          | 0.6473   |
  | 0.841         | 0.77  | 9500  | 0.8106          | 0.6379   |
  | 0.8302        | 0.81  | 10000 | 0.7966          | 0.6451   |
  | 0.8338        | 0.86  | 10500 | 0.8018          | 0.6440   |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  