readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: tiny-mlm-glue-mnli-custom-tokenizer
    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-custom-tokenizer
  
  This model is a fine-tuned version of [google/bert_uncased_L-2_H-128_A-2](https://huggingface.co/google/bert_uncased_L-2_H-128_A-2) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 6.1721
  
  ## 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 |
  |:-------------:|:-----:|:-----:|:---------------:|
  | 7.8162        | 0.4   | 500   | 7.1032          |
  | 6.9567        | 0.8   | 1000  | 7.0697          |
  | 6.8563        | 1.2   | 1500  | 7.0460          |
  | 6.7685        | 1.6   | 2000  | 7.0131          |
  | 6.6897        | 2.0   | 2500  | 6.9769          |
  | 6.5455        | 2.4   | 3000  | 6.9249          |
  | 6.482         | 2.8   | 3500  | 6.8552          |
  | 6.4153        | 3.2   | 4000  | 6.8445          |
  | 6.38          | 3.6   | 4500  | 6.7803          |
  | 6.4066        | 4.0   | 5000  | 6.8070          |
  | 6.2854        | 4.4   | 5500  | 6.7329          |
  | 6.2966        | 4.8   | 6000  | 6.7094          |
  | 6.1244        | 5.2   | 6500  | 6.6476          |
  | 6.1276        | 5.6   | 7000  | 6.6118          |
  | 6.0685        | 6.0   | 7500  | 6.5714          |
  | 5.98          | 6.4   | 8000  | 6.5522          |
  | 6.0174        | 6.8   | 8500  | 6.5093          |
  | 5.9451        | 7.2   | 9000  | 6.4866          |
  | 5.9681        | 7.6   | 9500  | 6.5238          |
  | 5.9246        | 8.0   | 10000 | 6.5340          |
  | 5.9219        | 8.4   | 10500 | 6.4727          |
  | 5.8812        | 8.8   | 11000 | 6.4483          |
  | 5.7815        | 9.2   | 11500 | 6.4402          |
  | 5.7938        | 9.6   | 12000 | 6.4124          |
  | 5.7934        | 10.0  | 12500 | 6.3908          |
  | 5.7332        | 10.4  | 13000 | 6.3861          |
  | 5.7628        | 10.8  | 13500 | 6.3638          |
  | 5.7259        | 11.2  | 14000 | 6.3345          |
  | 5.7505        | 11.6  | 14500 | 6.3117          |
  | 5.6441        | 12.0  | 15000 | 6.3118          |
  | 5.7058        | 12.4  | 15500 | 6.3116          |
  | 5.6017        | 12.8  | 16000 | 6.2728          |
  | 5.6424        | 13.2  | 16500 | 6.2790          |
  | 5.5799        | 13.6  | 17000 | 6.3034          |
  | 5.5625        | 14.0  | 17500 | 6.2580          |
  | 5.6015        | 14.4  | 18000 | 6.2607          |
  | 5.4884        | 14.8  | 18500 | 6.2535          |
  | 5.5117        | 15.2  | 19000 | 6.1960          |
  | 5.4919        | 15.6  | 19500 | 6.1907          |
  | 5.4624        | 16.0  | 20000 | 6.1838          |
  | 5.4721        | 16.4  | 20500 | 6.1461          |
  | 5.4833        | 16.8  | 21000 | 6.1251          |
  | 5.4404        | 17.2  | 21500 | 6.1725          |
  | 5.4487        | 17.6  | 22000 | 6.1417          |
  | 5.4499        | 18.0  | 22500 | 6.1721          |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  