readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  model-index:
  - name: small-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. -->
  
  # small-mlm-glue-mrpc-target-glue-qqp
  
  This model is a fine-tuned version of [muhtasham/small-mlm-glue-mrpc](https://huggingface.co/muhtasham/small-mlm-glue-mrpc) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3314
  - Accuracy: 0.8515
  - F1: 0.8122
  
  ## 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
  - training_steps: 5000
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
  | 0.4782        | 0.04  | 500  | 0.4205          | 0.7932   | 0.7493 |
  | 0.4193        | 0.09  | 1000 | 0.3913          | 0.8109   | 0.7696 |
  | 0.4021        | 0.13  | 1500 | 0.3765          | 0.8203   | 0.7732 |
  | 0.3853        | 0.18  | 2000 | 0.3753          | 0.8193   | 0.7874 |
  | 0.3788        | 0.22  | 2500 | 0.3609          | 0.8345   | 0.7965 |
  | 0.3614        | 0.26  | 3000 | 0.3482          | 0.8386   | 0.8000 |
  | 0.358         | 0.31  | 3500 | 0.3342          | 0.8500   | 0.8020 |
  | 0.3522        | 0.35  | 4000 | 0.3331          | 0.8481   | 0.8076 |
  | 0.3575        | 0.4   | 4500 | 0.3235          | 0.8533   | 0.8101 |
  | 0.3422        | 0.44  | 5000 | 0.3314          | 0.8515   | 0.8122 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  