readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - null
  model_index:
  - name: bert-base-uncased-multi-128
    results:
    - task:
        name: Masked Language Modeling
        type: fill-mask
  ---
  
  <!-- 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. -->
  
  # bert-base-uncased-multi-128
  
  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.7101
  
  ## 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: 5e-05
  - train_batch_size: 8
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 16
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss |
  |:-------------:|:-----:|:-----:|:---------------:|
  | 3.6636        | 1.0   | 812   | 3.2325          |
  | 3.2963        | 2.0   | 1624  | 3.1937          |
  | 3.1132        | 3.0   | 2436  | 3.2984          |
  | 2.9386        | 4.0   | 3248  | 3.2430          |
  | 2.7742        | 5.0   | 4060  | 3.1272          |
  | 2.5954        | 6.0   | 4872  | 3.1778          |
  | 2.501         | 7.0   | 5684  | 3.1649          |
  | 2.4073        | 8.0   | 6496  | 2.9395          |
  | 2.2933        | 9.0   | 7308  | 3.1262          |
  | 2.2218        | 10.0  | 8120  | 2.9994          |
  | 2.1558        | 11.0  | 8932  | 2.9922          |
  | 2.0873        | 12.0  | 9744  | 2.8414          |
  | 2.0104        | 13.0  | 10556 | 2.9351          |
  | 1.9364        | 14.0  | 11368 | 2.9253          |
  | 1.9045        | 15.0  | 12180 | 2.8701          |
  | 1.9152        | 16.0  | 12992 | 2.7101          |
  
  
  ### Framework versions
  
  - Transformers 4.8.2
  - Pytorch 1.7.1
  - Datasets 1.16.1
  - Tokenizers 0.10.3
  