readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: tiny-mlm-imdb
    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-imdb
  
  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: 3.5540
  
  ## 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 |
  |:-------------:|:-----:|:-----:|:---------------:|
  | 4.2358        | 0.16  | 500   | 3.8225          |
  | 4.1206        | 0.32  | 1000  | 3.7793          |
  | 4.0857        | 0.48  | 1500  | 3.7520          |
  | 4.0699        | 0.64  | 2000  | 3.7277          |
  | 4.0378        | 0.8   | 2500  | 3.7125          |
  | 4.0191        | 0.96  | 3000  | 3.7019          |
  | 3.9747        | 1.12  | 3500  | 3.6871          |
  | 3.9647        | 1.28  | 4000  | 3.6735          |
  | 3.956         | 1.44  | 4500  | 3.6773          |
  | 3.9574        | 1.6   | 5000  | 3.6580          |
  | 3.9408        | 1.76  | 5500  | 3.6435          |
  | 3.9421        | 1.92  | 6000  | 3.6419          |
  | 3.9265        | 2.08  | 6500  | 3.6343          |
  | 3.9198        | 2.24  | 7000  | 3.6306          |
  | 3.9205        | 2.4   | 7500  | 3.6198          |
  | 3.8985        | 2.56  | 8000  | 3.6158          |
  | 3.9167        | 2.72  | 8500  | 3.6091          |
  | 3.9111        | 2.88  | 9000  | 3.6073          |
  | 3.8882        | 3.04  | 9500  | 3.5922          |
  | 3.8761        | 3.2   | 10000 | 3.5908          |
  | 3.8603        | 3.36  | 10500 | 3.5841          |
  | 3.8621        | 3.52  | 11000 | 3.5835          |
  | 3.8332        | 3.68  | 11500 | 3.5883          |
  | 3.8523        | 3.84  | 12000 | 3.5798          |
  | 3.8449        | 4.0   | 12500 | 3.5771          |
  | 3.8284        | 4.16  | 13000 | 3.5653          |
  | 3.8253        | 4.32  | 13500 | 3.5701          |
  | 3.8021        | 4.48  | 14000 | 3.5681          |
  | 3.8316        | 4.64  | 14500 | 3.5537          |
  | 3.8318        | 4.8   | 15000 | 3.5609          |
  | 3.82          | 4.96  | 15500 | 3.5579          |
  | 3.8094        | 5.12  | 16000 | 3.5540          |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.12.1
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  