readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: small-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. -->
  
  # small-mlm-glue-mnli-custom-tokenizer
  
  This model is a fine-tuned version of [google/bert_uncased_L-4_H-512_A-8](https://huggingface.co/google/bert_uncased_L-4_H-512_A-8) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 5.6551
  
  ## 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 |
  |:-------------:|:-----:|:-----:|:---------------:|
  | 7.0308        | 0.4   | 500   | 6.6001          |
  | 6.346         | 0.8   | 1000  | 6.3998          |
  | 6.1061        | 1.2   | 1500  | 6.3170          |
  | 5.9586        | 1.6   | 2000  | 6.2799          |
  | 5.8773        | 2.0   | 2500  | 6.2034          |
  | 5.7403        | 2.4   | 3000  | 6.1609          |
  | 5.6602        | 2.8   | 3500  | 6.1113          |
  | 5.5809        | 3.2   | 4000  | 6.1267          |
  | 5.5663        | 3.6   | 4500  | 6.0647          |
  | 5.6266        | 4.0   | 5000  | 6.1090          |
  | 5.4756        | 4.4   | 5500  | 6.0302          |
  | 5.4905        | 4.8   | 6000  | 6.0292          |
  | 5.3179        | 5.2   | 6500  | 5.9758          |
  | 5.3375        | 5.6   | 7000  | 6.0125          |
  | 5.3035        | 6.0   | 7500  | 5.9495          |
  | 5.1918        | 6.4   | 8000  | 5.9537          |
  | 5.2499        | 6.8   | 8500  | 5.9100          |
  | 5.1905        | 7.2   | 9000  | 5.8620          |
  | 5.1787        | 7.6   | 9500  | 5.9296          |
  | 5.1534        | 8.0   | 10000 | 5.9442          |
  | 5.1396        | 8.4   | 10500 | 5.8609          |
  | 5.1272        | 8.8   | 11000 | 5.8358          |
  | 4.9615        | 9.2   | 11500 | 5.8617          |
  | 5.0062        | 9.6   | 12000 | 5.8043          |
  | 5.0131        | 10.0  | 12500 | 5.8119          |
  | 4.9326        | 10.4  | 13000 | 5.7851          |
  | 4.9655        | 10.8  | 13500 | 5.7792          |
  | 4.9256        | 11.2  | 14000 | 5.7843          |
  | 4.9195        | 11.6  | 14500 | 5.7652          |
  | 4.8299        | 12.0  | 15000 | 5.7606          |
  | 4.8748        | 12.4  | 15500 | 5.7577          |
  | 4.7588        | 12.8  | 16000 | 5.7048          |
  | 4.8185        | 13.2  | 16500 | 5.7245          |
  | 4.7679        | 13.6  | 17000 | 5.7402          |
  | 4.7377        | 14.0  | 17500 | 5.7034          |
  | 4.7403        | 14.4  | 18000 | 5.7054          |
  | 4.6628        | 14.8  | 18500 | 5.7203          |
  | 4.6801        | 15.2  | 19000 | 5.6798          |
  | 4.6014        | 15.6  | 19500 | 5.6931          |
  | 4.618         | 16.0  | 20000 | 5.6620          |
  | 4.6037        | 16.4  | 20500 | 5.6441          |
  | 4.6004        | 16.8  | 21000 | 5.6262          |
  | 4.5432        | 17.2  | 21500 | 5.6726          |
  | 4.576         | 17.6  | 22000 | 5.6322          |
  | 4.5568        | 18.0  | 22500 | 5.6551          |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  