readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: tiny-mlm-glue-rte-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-rte-target-glue-mnli
  
  This model is a fine-tuned version of [muhtasham/tiny-mlm-glue-rte](https://huggingface.co/muhtasham/tiny-mlm-glue-rte) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.7947
  - Accuracy: 0.6475
  
  ## 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 |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
  | 1.0719        | 0.04  | 500   | 1.0318          | 0.4653   |
  | 1.0131        | 0.08  | 1000  | 0.9779          | 0.5247   |
  | 0.9748        | 0.12  | 1500  | 0.9293          | 0.5769   |
  | 0.9415        | 0.16  | 2000  | 0.9073          | 0.5893   |
  | 0.9255        | 0.2   | 2500  | 0.8888          | 0.6011   |
  | 0.9168        | 0.24  | 3000  | 0.8789          | 0.6042   |
  | 0.8998        | 0.29  | 3500  | 0.8704          | 0.6077   |
  | 0.8948        | 0.33  | 4000  | 0.8624          | 0.6114   |
  | 0.8791        | 0.37  | 4500  | 0.8571          | 0.6176   |
  | 0.8832        | 0.41  | 5000  | 0.8501          | 0.6192   |
  | 0.8742        | 0.45  | 5500  | 0.8423          | 0.6247   |
  | 0.87          | 0.49  | 6000  | 0.8410          | 0.6280   |
  | 0.874         | 0.53  | 6500  | 0.8322          | 0.6328   |
  | 0.8623        | 0.57  | 7000  | 0.8342          | 0.6296   |
  | 0.8563        | 0.61  | 7500  | 0.8192          | 0.6394   |
  | 0.8562        | 0.65  | 8000  | 0.8194          | 0.6367   |
  | 0.8504        | 0.69  | 8500  | 0.8284          | 0.6327   |
  | 0.8519        | 0.73  | 9000  | 0.8044          | 0.6424   |
  | 0.8436        | 0.77  | 9500  | 0.8175          | 0.6354   |
  | 0.8349        | 0.81  | 10000 | 0.8015          | 0.6438   |
  | 0.8372        | 0.86  | 10500 | 0.8094          | 0.6368   |
  | 0.835         | 0.9   | 11000 | 0.7958          | 0.6469   |
  | 0.8291        | 0.94  | 11500 | 0.7922          | 0.6479   |
  | 0.8274        | 0.98  | 12000 | 0.7938          | 0.6449   |
  | 0.8158        | 1.02  | 12500 | 0.7971          | 0.6450   |
  | 0.8111        | 1.06  | 13000 | 0.7947          | 0.6475   |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  