readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: tiny-mlm-glue-mnli-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-mnli-target-glue-mnli
  
  This model is a fine-tuned version of [muhtasham/tiny-mlm-glue-mnli](https://huggingface.co/muhtasham/tiny-mlm-glue-mnli) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.8010
  - Accuracy: 0.6426
  
  ## 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 |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
  | 1.0743        | 0.04  | 500   | 1.0281          | 0.4738   |
  | 1.0045        | 0.08  | 1000  | 0.9576          | 0.5522   |
  | 0.9565        | 0.12  | 1500  | 0.9155          | 0.5802   |
  | 0.929         | 0.16  | 2000  | 0.8997          | 0.5936   |
  | 0.9205        | 0.2   | 2500  | 0.8868          | 0.6011   |
  | 0.9127        | 0.24  | 3000  | 0.8733          | 0.6066   |
  | 0.8972        | 0.29  | 3500  | 0.8659          | 0.6121   |
  | 0.8908        | 0.33  | 4000  | 0.8527          | 0.6202   |
  | 0.8747        | 0.37  | 4500  | 0.8507          | 0.6200   |
  | 0.8778        | 0.41  | 5000  | 0.8418          | 0.6254   |
  | 0.869         | 0.45  | 5500  | 0.8373          | 0.6262   |
  | 0.8647        | 0.49  | 6000  | 0.8339          | 0.6318   |
  | 0.8677        | 0.53  | 6500  | 0.8268          | 0.6310   |
  | 0.8576        | 0.57  | 7000  | 0.8269          | 0.6323   |
  | 0.852         | 0.61  | 7500  | 0.8126          | 0.6396   |
  | 0.8525        | 0.65  | 8000  | 0.8119          | 0.6399   |
  | 0.8441        | 0.69  | 8500  | 0.8230          | 0.6319   |
  | 0.8492        | 0.73  | 9000  | 0.7975          | 0.6486   |
  | 0.8394        | 0.77  | 9500  | 0.8088          | 0.6373   |
  | 0.8294        | 0.81  | 10000 | 0.7949          | 0.6460   |
  | 0.8341        | 0.86  | 10500 | 0.8010          | 0.6426   |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  