readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  model-index:
  - name: tiny-mlm-glue-rte-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-rte-target-glue-qqp
  
  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: 0.4155
  - Accuracy: 0.7949
  - F1: 0.7691
  
  ## 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     |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
  | 0.5776        | 0.04  | 500   | 0.5189          | 0.7264   | 0.6855 |
  | 0.5081        | 0.09  | 1000  | 0.4824          | 0.7519   | 0.7059 |
  | 0.4951        | 0.13  | 1500  | 0.4940          | 0.7377   | 0.7141 |
  | 0.4792        | 0.18  | 2000  | 0.4704          | 0.7526   | 0.7221 |
  | 0.4722        | 0.22  | 2500  | 0.4571          | 0.7618   | 0.7277 |
  | 0.4557        | 0.26  | 3000  | 0.4496          | 0.7677   | 0.7346 |
  | 0.4567        | 0.31  | 3500  | 0.4480          | 0.7677   | 0.7378 |
  | 0.4497        | 0.35  | 4000  | 0.4502          | 0.7655   | 0.7386 |
  | 0.4503        | 0.4   | 4500  | 0.4426          | 0.7712   | 0.7432 |
  | 0.4412        | 0.44  | 5000  | 0.4216          | 0.7889   | 0.7501 |
  | 0.4291        | 0.48  | 5500  | 0.4284          | 0.7837   | 0.7515 |
  | 0.4293        | 0.53  | 6000  | 0.4075          | 0.8004   | 0.7577 |
  | 0.4241        | 0.57  | 6500  | 0.4230          | 0.7879   | 0.7559 |
  | 0.4253        | 0.62  | 7000  | 0.4067          | 0.8002   | 0.7601 |
  | 0.4166        | 0.66  | 7500  | 0.4083          | 0.8026   | 0.7646 |
  | 0.4302        | 0.7   | 8000  | 0.4121          | 0.7964   | 0.7624 |
  | 0.4206        | 0.75  | 8500  | 0.3993          | 0.8051   | 0.7667 |
  | 0.4147        | 0.79  | 9000  | 0.4202          | 0.7884   | 0.7610 |
  | 0.4117        | 0.84  | 9500  | 0.3915          | 0.8094   | 0.7677 |
  | 0.4131        | 0.88  | 10000 | 0.3863          | 0.8156   | 0.7735 |
  | 0.4089        | 0.92  | 10500 | 0.3832          | 0.8157   | 0.7713 |
  | 0.4086        | 0.97  | 11000 | 0.3836          | 0.8180   | 0.7732 |
  | 0.406         | 1.01  | 11500 | 0.4042          | 0.8018   | 0.7707 |
  | 0.3854        | 1.06  | 12000 | 0.3819          | 0.8182   | 0.7763 |
  | 0.3952        | 1.1   | 12500 | 0.3836          | 0.8149   | 0.7771 |
  | 0.3827        | 1.14  | 13000 | 0.3898          | 0.8134   | 0.7766 |
  | 0.3719        | 1.19  | 13500 | 0.4155          | 0.7949   | 0.7691 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  