readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: medium-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. -->
  
  # medium-mlm-imdb
  
  This model is a fine-tuned version of [google/bert_uncased_L-8_H-512_A-8](https://huggingface.co/google/bert_uncased_L-8_H-512_A-8) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.1889
  
  ## 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 |
  |:-------------:|:-----:|:-----:|:---------------:|
  | 2.5116        | 0.16  | 500   | 2.3298          |
  | 2.4448        | 0.32  | 1000  | 2.3157          |
  | 2.4362        | 0.48  | 1500  | 2.2987          |
  | 2.4287        | 0.64  | 2000  | 2.2878          |
  | 2.4125        | 0.8   | 2500  | 2.2693          |
  | 2.4066        | 0.96  | 3000  | 2.2666          |
  | 2.352         | 1.12  | 3500  | 2.2590          |
  | 2.3406        | 1.28  | 4000  | 2.2501          |
  | 2.3443        | 1.44  | 4500  | 2.2433          |
  | 2.3331        | 1.6   | 5000  | 2.2373          |
  | 2.3247        | 1.76  | 5500  | 2.2357          |
  | 2.3343        | 1.92  | 6000  | 2.2332          |
  | 2.3092        | 2.08  | 6500  | 2.2334          |
  | 2.3034        | 2.24  | 7000  | 2.2319          |
  | 2.2984        | 2.4   | 7500  | 2.2254          |
  | 2.2794        | 2.56  | 8000  | 2.2186          |
  | 2.3028        | 2.72  | 8500  | 2.2130          |
  | 2.3047        | 2.88  | 9000  | 2.2156          |
  | 2.2785        | 3.04  | 9500  | 2.2084          |
  | 2.2562        | 3.2   | 10000 | 2.2105          |
  | 2.2553        | 3.36  | 10500 | 2.2034          |
  | 2.2626        | 3.52  | 11000 | 2.2024          |
  | 2.2313        | 3.68  | 11500 | 2.2056          |
  | 2.2514        | 3.84  | 12000 | 2.1980          |
  | 2.2462        | 4.0   | 12500 | 2.2052          |
  | 2.2143        | 4.16  | 13000 | 2.1928          |
  | 2.2199        | 4.32  | 13500 | 2.1972          |
  | 2.2045        | 4.48  | 14000 | 2.2014          |
  | 2.2246        | 4.64  | 14500 | 2.1885          |
  | 2.2272        | 4.8   | 15000 | 2.1895          |
  | 2.2213        | 4.96  | 15500 | 2.1976          |
  | 2.2074        | 5.12  | 16000 | 2.1889          |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.12.1
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  