readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: tiny-mlm-glue-stsb-target-glue-mnli
    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-stsb-target-glue-mnli
  
  This model is a fine-tuned version of [muhtasham/tiny-mlm-glue-stsb](https://huggingface.co/muhtasham/tiny-mlm-glue-stsb) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.8112
  - Accuracy: 0.6365
  
  ## 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 |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
  | 1.0767        | 0.04  | 500   | 1.0354          | 0.4644   |
  | 1.0091        | 0.08  | 1000  | 0.9646          | 0.5496   |
  | 0.9629        | 0.12  | 1500  | 0.9236          | 0.5798   |
  | 0.9384        | 0.16  | 2000  | 0.9054          | 0.5916   |
  | 0.9254        | 0.2   | 2500  | 0.8894          | 0.5995   |
  | 0.9167        | 0.24  | 3000  | 0.8788          | 0.6028   |
  | 0.9013        | 0.29  | 3500  | 0.8707          | 0.6104   |
  | 0.8962        | 0.33  | 4000  | 0.8603          | 0.6132   |
  | 0.8802        | 0.37  | 4500  | 0.8561          | 0.6185   |
  | 0.8834        | 0.41  | 5000  | 0.8490          | 0.6220   |
  | 0.8734        | 0.45  | 5500  | 0.8427          | 0.6227   |
  | 0.8721        | 0.49  | 6000  | 0.8399          | 0.6278   |
  | 0.8739        | 0.53  | 6500  | 0.8336          | 0.6331   |
  | 0.8654        | 0.57  | 7000  | 0.8345          | 0.6294   |
  | 0.8579        | 0.61  | 7500  | 0.8192          | 0.6375   |
  | 0.8567        | 0.65  | 8000  | 0.8191          | 0.6348   |
  | 0.8517        | 0.69  | 8500  | 0.8275          | 0.6315   |
  | 0.8528        | 0.73  | 9000  | 0.8060          | 0.6433   |
  | 0.8448        | 0.77  | 9500  | 0.8152          | 0.6355   |
  | 0.8361        | 0.81  | 10000 | 0.8026          | 0.6415   |
  | 0.8398        | 0.86  | 10500 | 0.8112          | 0.6365   |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  