readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: tiny-mlm-glue-wnli
    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
  
  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: 0.7902
  
  ## 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 |
  |:-------------:|:------:|:----:|:---------------:|
  | 3.5021        | 6.25   | 500  | 2.8676          |
  | 2.9602        | 12.5   | 1000 | 2.5328          |
  | 2.6906        | 18.75  | 1500 | 2.3640          |
  | 2.4167        | 25.0   | 2000 | 2.0918          |
  | 2.2699        | 31.25  | 2500 | 2.1182          |
  | 2.0933        | 37.5   | 3000 | 1.8802          |
  | 1.9399        | 43.75  | 3500 | 1.8979          |
  | 1.7961        | 50.0   | 4000 | 1.5276          |
  | 1.6738        | 56.25  | 4500 | 1.5327          |
  | 1.5784        | 62.5   | 5000 | 1.2767          |
  | 1.4405        | 68.75  | 5500 | 1.3593          |
  | 1.3428        | 75.0   | 6000 | 0.9772          |
  | 1.3257        | 81.25  | 6500 | 1.2789          |
  | 1.1988        | 87.5   | 7000 | 0.9494          |
  | 1.1275        | 93.75  | 7500 | 0.8278          |
  | 1.0854        | 100.0  | 8000 | 0.6301          |
  | 1.0275        | 106.25 | 8500 | 0.8044          |
  | 0.9714        | 112.5  | 9000 | 0.7544          |
  | 0.9019        | 118.75 | 9500 | 0.7902          |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  