readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: small-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. -->
  
  # small-mlm-imdb
  
  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: 2.3673
  
  ## 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 |
  |:-------------:|:-----:|:-----:|:---------------:|
  | 2.7542        | 0.16  | 500   | 2.5445          |
  | 2.6734        | 0.32  | 1000  | 2.5191          |
  | 2.6552        | 0.48  | 1500  | 2.4976          |
  | 2.6481        | 0.64  | 2000  | 2.4866          |
  | 2.6291        | 0.8   | 2500  | 2.4599          |
  | 2.6134        | 0.96  | 3000  | 2.4585          |
  | 2.5627        | 1.12  | 3500  | 2.4476          |
  | 2.5564        | 1.28  | 4000  | 2.4340          |
  | 2.5493        | 1.44  | 4500  | 2.4354          |
  | 2.5435        | 1.6   | 5000  | 2.4307          |
  | 2.5352        | 1.76  | 5500  | 2.4224          |
  | 2.5445        | 1.92  | 6000  | 2.4167          |
  | 2.5191        | 2.08  | 6500  | 2.4175          |
  | 2.5143        | 2.24  | 7000  | 2.4149          |
  | 2.5059        | 2.4   | 7500  | 2.4117          |
  | 2.4865        | 2.56  | 8000  | 2.4063          |
  | 2.5113        | 2.72  | 8500  | 2.3976          |
  | 2.5115        | 2.88  | 9000  | 2.3959          |
  | 2.485         | 3.04  | 9500  | 2.3917          |
  | 2.4652        | 3.2   | 10000 | 2.3908          |
  | 2.4569        | 3.36  | 10500 | 2.3877          |
  | 2.4706        | 3.52  | 11000 | 2.3836          |
  | 2.4375        | 3.68  | 11500 | 2.3870          |
  | 2.4556        | 3.84  | 12000 | 2.3819          |
  | 2.4487        | 4.0   | 12500 | 2.3842          |
  | 2.4233        | 4.16  | 13000 | 2.3731          |
  | 2.4238        | 4.32  | 13500 | 2.3801          |
  | 2.4051        | 4.48  | 14000 | 2.3809          |
  | 2.432         | 4.64  | 14500 | 2.3641          |
  | 2.428         | 4.8   | 15000 | 2.3686          |
  | 2.4248        | 4.96  | 15500 | 2.3741          |
  | 2.4109        | 5.12  | 16000 | 2.3673          |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.12.1
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  