readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: tiny-mlm-glue-qnli-target-glue-sst2
    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-qnli-target-glue-sst2
  
  This model is a fine-tuned version of [muhtasham/tiny-mlm-glue-qnli](https://huggingface.co/muhtasham/tiny-mlm-glue-qnli) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.5008
  - Accuracy: 0.8211
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 0.5757        | 0.24  | 500  | 0.4901          | 0.7775   |
  | 0.4436        | 0.48  | 1000 | 0.4673          | 0.7833   |
  | 0.3947        | 0.71  | 1500 | 0.4434          | 0.7970   |
  | 0.3751        | 0.95  | 2000 | 0.4601          | 0.7970   |
  | 0.3326        | 1.19  | 2500 | 0.4463          | 0.8005   |
  | 0.316         | 1.43  | 3000 | 0.4510          | 0.8005   |
  | 0.2981        | 1.66  | 3500 | 0.4367          | 0.8142   |
  | 0.2929        | 1.9   | 4000 | 0.4383          | 0.8108   |
  | 0.2746        | 2.14  | 4500 | 0.4873          | 0.8016   |
  | 0.256         | 2.38  | 5000 | 0.4395          | 0.8165   |
  | 0.246         | 2.61  | 5500 | 0.4444          | 0.8280   |
  | 0.2522        | 2.85  | 6000 | 0.4478          | 0.8245   |
  | 0.2371        | 3.09  | 6500 | 0.4556          | 0.8291   |
  | 0.2299        | 3.33  | 7000 | 0.4655          | 0.8326   |
  | 0.2143        | 3.56  | 7500 | 0.4581          | 0.8314   |
  | 0.2153        | 3.8   | 8000 | 0.4869          | 0.8291   |
  | 0.2134        | 4.04  | 8500 | 0.5008          | 0.8211   |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  