readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  model-index:
  - name: tiny-mlm-glue-mrpc-target-glue-qqp
    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-qqp
  
  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: 0.4096
  - Accuracy: 0.7995
  - F1: 0.7718
  
  ## 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 | F1     |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
  | 0.5796        | 0.04  | 500   | 0.5174          | 0.7297   | 0.6813 |
  | 0.5102        | 0.09  | 1000  | 0.4804          | 0.7541   | 0.7035 |
  | 0.4957        | 0.13  | 1500  | 0.4916          | 0.7412   | 0.7152 |
  | 0.4798        | 0.18  | 2000  | 0.4679          | 0.7549   | 0.7221 |
  | 0.4728        | 0.22  | 2500  | 0.4563          | 0.7624   | 0.7270 |
  | 0.4569        | 0.26  | 3000  | 0.4501          | 0.7673   | 0.7340 |
  | 0.4583        | 0.31  | 3500  | 0.4480          | 0.7682   | 0.7375 |
  | 0.4502        | 0.35  | 4000  | 0.4498          | 0.7665   | 0.7387 |
  | 0.4514        | 0.4   | 4500  | 0.4452          | 0.7681   | 0.7410 |
  | 0.4416        | 0.44  | 5000  | 0.4209          | 0.7884   | 0.7491 |
  | 0.4297        | 0.48  | 5500  | 0.4288          | 0.7826   | 0.7502 |
  | 0.4299        | 0.53  | 6000  | 0.4069          | 0.8001   | 0.7559 |
  | 0.4248        | 0.57  | 6500  | 0.4194          | 0.7896   | 0.7547 |
  | 0.4257        | 0.62  | 7000  | 0.4063          | 0.7998   | 0.7582 |
  | 0.418         | 0.66  | 7500  | 0.4059          | 0.8038   | 0.7639 |
  | 0.4306        | 0.7   | 8000  | 0.4111          | 0.7964   | 0.7615 |
  | 0.4212        | 0.75  | 8500  | 0.3990          | 0.8065   | 0.7672 |
  | 0.4143        | 0.79  | 9000  | 0.4227          | 0.7875   | 0.7604 |
  | 0.4121        | 0.84  | 9500  | 0.3906          | 0.8098   | 0.7667 |
  | 0.4138        | 0.88  | 10000 | 0.3872          | 0.8152   | 0.7725 |
  | 0.4082        | 0.92  | 10500 | 0.3843          | 0.8148   | 0.7700 |
  | 0.4084        | 0.97  | 11000 | 0.3863          | 0.8170   | 0.7740 |
  | 0.4067        | 1.01  | 11500 | 0.4001          | 0.8037   | 0.7707 |
  | 0.3854        | 1.06  | 12000 | 0.3814          | 0.8182   | 0.7756 |
  | 0.3945        | 1.1   | 12500 | 0.3861          | 0.8132   | 0.7761 |
  | 0.3831        | 1.14  | 13000 | 0.3917          | 0.8110   | 0.7750 |
  | 0.3722        | 1.19  | 13500 | 0.4096          | 0.7995   | 0.7718 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  