readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: tiny-mlm-glue-rte-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-rte-target-glue-sst2
  
  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: 0.4848
  - Accuracy: 0.8314
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 0.5758        | 0.24  | 500  | 0.4891          | 0.7821   |
  | 0.4444        | 0.48  | 1000 | 0.4679          | 0.7856   |
  | 0.3956        | 0.71  | 1500 | 0.4446          | 0.8016   |
  | 0.3754        | 0.95  | 2000 | 0.4579          | 0.7993   |
  | 0.3336        | 1.19  | 2500 | 0.4468          | 0.8039   |
  | 0.3169        | 1.43  | 3000 | 0.4499          | 0.8028   |
  | 0.2982        | 1.66  | 3500 | 0.4385          | 0.8131   |
  | 0.2933        | 1.9   | 4000 | 0.4380          | 0.8108   |
  | 0.2753        | 2.14  | 4500 | 0.4841          | 0.8050   |
  | 0.2569        | 2.38  | 5000 | 0.4376          | 0.8177   |
  | 0.2466        | 2.61  | 5500 | 0.4397          | 0.8245   |
  | 0.2527        | 2.85  | 6000 | 0.4462          | 0.8234   |
  | 0.2377        | 3.09  | 6500 | 0.4545          | 0.8337   |
  | 0.2303        | 3.33  | 7000 | 0.4655          | 0.8268   |
  | 0.2151        | 3.56  | 7500 | 0.4566          | 0.8291   |
  | 0.2156        | 3.8   | 8000 | 0.4848          | 0.8314   |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  