readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: base-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. -->
  
  # base-mlm-imdb
  
  This model is a fine-tuned version of [google/bert_uncased_L-12_H-768_A-12](https://huggingface.co/google/bert_uncased_L-12_H-768_A-12) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.9103
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|
  | 2.1149        | 0.16  | 500  | 1.9627          |
  | 2.0674        | 0.32  | 1000 | 1.9620          |
  | 2.0582        | 0.48  | 1500 | 1.9502          |
  | 2.0542        | 0.64  | 2000 | 1.9418          |
  | 2.0398        | 0.8   | 2500 | 1.9223          |
  | 2.037         | 0.96  | 3000 | 1.9220          |
  | 1.9831        | 1.12  | 3500 | 1.9247          |
  | 1.972         | 1.28  | 4000 | 1.9123          |
  | 1.9708        | 1.44  | 4500 | 1.9122          |
  | 1.967         | 1.6   | 5000 | 1.9097          |
  | 1.9582        | 1.76  | 5500 | 1.9085          |
  | 1.9715        | 1.92  | 6000 | 1.9099          |
  | 1.9459        | 2.08  | 6500 | 1.9113          |
  | 1.9384        | 2.24  | 7000 | 1.9103          |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.12.1
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  