readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  model-index:
  - name: tiny-mlm-glue-cola-custom-tokenizer-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-cola-custom-tokenizer-target-glue-qqp
  
  This model is a fine-tuned version of [muhtasham/tiny-mlm-glue-cola-custom-tokenizer](https://huggingface.co/muhtasham/tiny-mlm-glue-cola-custom-tokenizer) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4522
  - Accuracy: 0.7694
  - F1: 0.7176
  
  ## 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     |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
  | 0.6113        | 0.04  | 500   | 0.5700          | 0.6848   | 0.5805 |
  | 0.5608        | 0.09  | 1000  | 0.5332          | 0.7140   | 0.6093 |
  | 0.5442        | 0.13  | 1500  | 0.5218          | 0.7215   | 0.6596 |
  | 0.5278        | 0.18  | 2000  | 0.5059          | 0.7337   | 0.6510 |
  | 0.5193        | 0.22  | 2500  | 0.4961          | 0.7402   | 0.6579 |
  | 0.5085        | 0.26  | 3000  | 0.4918          | 0.7413   | 0.6695 |
  | 0.5049        | 0.31  | 3500  | 0.4851          | 0.7464   | 0.6760 |
  | 0.5024        | 0.35  | 4000  | 0.4900          | 0.7433   | 0.6854 |
  | 0.505         | 0.4   | 4500  | 0.4799          | 0.7500   | 0.6846 |
  | 0.4942        | 0.44  | 5000  | 0.4715          | 0.7568   | 0.6800 |
  | 0.4826        | 0.48  | 5500  | 0.4733          | 0.7528   | 0.6936 |
  | 0.4898        | 0.53  | 6000  | 0.4634          | 0.7638   | 0.6684 |
  | 0.4789        | 0.57  | 6500  | 0.4643          | 0.7617   | 0.6904 |
  | 0.4721        | 0.62  | 7000  | 0.4594          | 0.7652   | 0.6810 |
  | 0.4742        | 0.66  | 7500  | 0.4654          | 0.7616   | 0.6937 |
  | 0.4828        | 0.7   | 8000  | 0.4608          | 0.7648   | 0.6997 |
  | 0.4758        | 0.75  | 8500  | 0.4538          | 0.7680   | 0.6891 |
  | 0.4697        | 0.79  | 9000  | 0.4614          | 0.7626   | 0.7067 |
  | 0.466         | 0.84  | 9500  | 0.4497          | 0.7718   | 0.6838 |
  | 0.4685        | 0.88  | 10000 | 0.4491          | 0.7714   | 0.6765 |
  | 0.4629        | 0.92  | 10500 | 0.4502          | 0.7708   | 0.6595 |
  | 0.4617        | 0.97  | 11000 | 0.4473          | 0.7723   | 0.6809 |
  | 0.4606        | 1.01  | 11500 | 0.4569          | 0.7668   | 0.7114 |
  | 0.4467        | 1.06  | 12000 | 0.4482          | 0.7752   | 0.6727 |
  | 0.4537        | 1.1   | 12500 | 0.4468          | 0.7722   | 0.7130 |
  | 0.454         | 1.14  | 13000 | 0.4545          | 0.7711   | 0.7131 |
  | 0.4395        | 1.19  | 13500 | 0.4522          | 0.7694   | 0.7176 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  