readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: tiny-mlm-snli-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-snli-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: 4.8264
  
  ## 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 |
  |:-------------:|:-----:|:-----:|:---------------:|
  | 6.5934        | 0.4   | 500   | 6.1299          |
  | 5.5915        | 0.8   | 1000  | 6.0987          |
  | 5.4106        | 1.2   | 1500  | 6.0209          |
  | 5.3188        | 1.6   | 2000  | 5.9610          |
  | 5.1738        | 2.0   | 2500  | 5.8186          |
  | 5.0521        | 2.4   | 3000  | 5.7991          |
  | 4.9494        | 2.8   | 3500  | 5.7584          |
  | 4.9176        | 3.2   | 4000  | 5.6663          |
  | 4.8419        | 3.6   | 4500  | 5.6272          |
  | 4.6759        | 4.0   | 5000  | 5.5572          |
  | 4.6021        | 4.4   | 5500  | 5.4644          |
  | 4.6077        | 4.8   | 6000  | 5.4168          |
  | 4.4571        | 5.2   | 6500  | 5.3577          |
  | 4.4012        | 5.6   | 7000  | 5.3301          |
  | 4.3231        | 6.0   | 7500  | 5.2220          |
  | 4.2708        | 6.4   | 8000  | 5.2296          |
  | 4.2149        | 6.8   | 8500  | 5.1176          |
  | 4.1028        | 7.2   | 9000  | 5.1298          |
  | 4.1042        | 7.6   | 9500  | 5.0949          |
  | 4.0501        | 8.0   | 10000 | 5.0850          |
  | 4.012         | 8.4   | 10500 | 5.0018          |
  | 3.875         | 8.8   | 11000 | 5.0539          |
  | 3.8863        | 9.2   | 11500 | 4.8985          |
  | 3.8032        | 9.6   | 12000 | 4.9226          |
  | 3.8501        | 10.0  | 12500 | 4.9202          |
  | 3.6744        | 10.4  | 13000 | 4.8908          |
  | 3.6515        | 10.8  | 13500 | 4.9305          |
  | 3.6525        | 11.2  | 14000 | 4.8675          |
  | 3.6416        | 11.6  | 14500 | 4.8610          |
  | 3.5686        | 12.0  | 15000 | 4.6993          |
  | 3.5437        | 12.4  | 15500 | 4.8085          |
  | 3.4837        | 12.8  | 16000 | 4.7654          |
  | 3.4553        | 13.2  | 16500 | 4.8264          |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  