readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  model-index:
  - name: tiny-mlm-glue-stsb-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-stsb-target-glue-qqp
  
  This model is a fine-tuned version of [muhtasham/tiny-mlm-glue-stsb](https://huggingface.co/muhtasham/tiny-mlm-glue-stsb) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3868
  - Accuracy: 0.8128
  - F1: 0.7756
  
  ## 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     |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
  | 0.5792        | 0.04  | 500   | 0.5164          | 0.7290   | 0.6761 |
  | 0.5106        | 0.09  | 1000  | 0.4848          | 0.7490   | 0.7008 |
  | 0.4974        | 0.13  | 1500  | 0.4907          | 0.7414   | 0.7142 |
  | 0.4818        | 0.18  | 2000  | 0.4670          | 0.7555   | 0.7216 |
  | 0.4734        | 0.22  | 2500  | 0.4576          | 0.7624   | 0.7274 |
  | 0.4564        | 0.26  | 3000  | 0.4486          | 0.7675   | 0.7329 |
  | 0.4578        | 0.31  | 3500  | 0.4455          | 0.7688   | 0.7361 |
  | 0.451         | 0.35  | 4000  | 0.4490          | 0.7672   | 0.7383 |
  | 0.4511        | 0.4   | 4500  | 0.4401          | 0.7720   | 0.7426 |
  | 0.4419        | 0.44  | 5000  | 0.4201          | 0.7888   | 0.7491 |
  | 0.4308        | 0.48  | 5500  | 0.4266          | 0.7843   | 0.7507 |
  | 0.4308        | 0.53  | 6000  | 0.4077          | 0.8005   | 0.7566 |
  | 0.4249        | 0.57  | 6500  | 0.4182          | 0.7913   | 0.7558 |
  | 0.4256        | 0.62  | 7000  | 0.4051          | 0.8008   | 0.7582 |
  | 0.4179        | 0.66  | 7500  | 0.4064          | 0.8037   | 0.7630 |
  | 0.4314        | 0.7   | 8000  | 0.4105          | 0.7963   | 0.7607 |
  | 0.4202        | 0.75  | 8500  | 0.3970          | 0.8064   | 0.7656 |
  | 0.4152        | 0.79  | 9000  | 0.4204          | 0.7894   | 0.7615 |
  | 0.4121        | 0.84  | 9500  | 0.3908          | 0.8099   | 0.7667 |
  | 0.4135        | 0.88  | 10000 | 0.3863          | 0.8151   | 0.7707 |
  | 0.4091        | 0.92  | 10500 | 0.3839          | 0.8149   | 0.7702 |
  | 0.4084        | 0.97  | 11000 | 0.3837          | 0.8179   | 0.7719 |
  | 0.4068        | 1.01  | 11500 | 0.3990          | 0.8048   | 0.7712 |
  | 0.3861        | 1.06  | 12000 | 0.3821          | 0.8173   | 0.7743 |
  | 0.3955        | 1.1   | 12500 | 0.3868          | 0.8128   | 0.7756 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  