readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: tiny-mlm-glue-wnli-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-wnli-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: 2.5277
  
  ## 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 |
  |:-------------:|:------:|:----:|:---------------:|
  | 6.6853        | 6.25   | 500  | 6.1267          |
  | 5.7417        | 12.5   | 1000 | 5.9357          |
  | 5.6014        | 18.75  | 1500 | 5.7487          |
  | 5.4076        | 25.0   | 2000 | 5.2954          |
  | 5.1906        | 31.25  | 2500 | 5.1483          |
  | 4.9775        | 37.5   | 3000 | 5.2707          |
  | 4.7267        | 43.75  | 3500 | 4.5667          |
  | 4.4882        | 50.0   | 4000 | 4.7044          |
  | 4.2548        | 56.25  | 4500 | 4.0688          |
  | 4.0119        | 62.5   | 5000 | 3.8329          |
  | 3.7807        | 68.75  | 5500 | 3.7323          |
  | 3.5306        | 75.0   | 6000 | 3.2662          |
  | 3.3206        | 81.25  | 6500 | 3.2223          |
  | 3.1002        | 87.5   | 7000 | 3.1473          |
  | 2.9093        | 93.75  | 7500 | 2.7988          |
  | 2.7146        | 100.0  | 8000 | 2.3988          |
  | 2.5981        | 106.25 | 8500 | 2.5495          |
  | 2.4007        | 112.5  | 9000 | 2.4030          |
  | 2.2446        | 118.75 | 9500 | 2.5277          |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  