readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: tiny-mlm-glue-mrpc-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-mrpc-target-glue-mnli
  
  This model is a fine-tuned version of [muhtasham/tiny-mlm-glue-mrpc](https://huggingface.co/muhtasham/tiny-mlm-glue-mrpc) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.8094
  - Accuracy: 0.6373
  
  ## 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 |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
  | 1.0737        | 0.04  | 500   | 1.0366          | 0.4615   |
  | 1.0169        | 0.08  | 1000  | 0.9833          | 0.5194   |
  | 0.9799        | 0.12  | 1500  | 0.9344          | 0.5719   |
  | 0.9452        | 0.16  | 2000  | 0.9106          | 0.5879   |
  | 0.9293        | 0.2   | 2500  | 0.8905          | 0.5962   |
  | 0.9189        | 0.24  | 3000  | 0.8801          | 0.6026   |
  | 0.9017        | 0.29  | 3500  | 0.8705          | 0.6103   |
  | 0.896         | 0.33  | 4000  | 0.8619          | 0.6178   |
  | 0.881         | 0.37  | 4500  | 0.8574          | 0.6211   |
  | 0.8854        | 0.41  | 5000  | 0.8495          | 0.6201   |
  | 0.8756        | 0.45  | 5500  | 0.8434          | 0.6223   |
  | 0.8713        | 0.49  | 6000  | 0.8410          | 0.6263   |
  | 0.8757        | 0.53  | 6500  | 0.8337          | 0.6301   |
  | 0.8624        | 0.57  | 7000  | 0.8363          | 0.6284   |
  | 0.8576        | 0.61  | 7500  | 0.8203          | 0.6356   |
  | 0.8583        | 0.65  | 8000  | 0.8188          | 0.6378   |
  | 0.8523        | 0.69  | 8500  | 0.8294          | 0.6304   |
  | 0.8533        | 0.73  | 9000  | 0.8052          | 0.6429   |
  | 0.8448        | 0.77  | 9500  | 0.8180          | 0.6356   |
  | 0.8368        | 0.81  | 10000 | 0.8030          | 0.6399   |
  | 0.8389        | 0.86  | 10500 | 0.8094          | 0.6373   |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  