readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: small-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. -->
  
  # small-mlm-glue-wnli-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: 0.2966
  
  ## 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 |
  |:-------------:|:------:|:----:|:---------------:|
  | 5.7189        | 6.25   | 500  | 5.1827          |
  | 4.4287        | 12.5   | 1000 | 4.3325          |
  | 3.5065        | 18.75  | 1500 | 3.3465          |
  | 2.6482        | 25.0   | 2000 | 2.4543          |
  | 1.8682        | 31.25  | 2500 | 1.8391          |
  | 1.405         | 37.5   | 3000 | 1.3834          |
  | 0.9971        | 43.75  | 3500 | 1.0132          |
  | 0.7485        | 50.0   | 4000 | 0.8970          |
  | 0.5753        | 56.25  | 4500 | 0.4850          |
  | 0.4756        | 62.5   | 5000 | 0.4589          |
  | 0.3926        | 68.75  | 5500 | 0.7330          |
  | 0.3287        | 75.0   | 6000 | 0.3611          |
  | 0.2929        | 81.25  | 6500 | 0.3802          |
  | 0.2477        | 87.5   | 7000 | 0.2649          |
  | 0.2316        | 93.75  | 7500 | 0.3877          |
  | 0.2207        | 100.0  | 8000 | 0.1159          |
  | 0.2015        | 106.25 | 8500 | 0.2502          |
  | 0.1803        | 112.5  | 9000 | 0.1365          |
  | 0.1544        | 118.75 | 9500 | 0.2966          |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  