readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: bert-base-uncased-lm-all
    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. -->
  
  # bert-base-uncased-lm-all
  
  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: 0.8646
  
  ## 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: 32
  - 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 |
  |:-------------:|:-----:|:-----:|:---------------:|
  | 1.6625        | 1.0   | 1194  | 1.3270          |
  | 1.3001        | 2.0   | 2388  | 1.1745          |
  | 1.1694        | 3.0   | 3582  | 1.1133          |
  | 1.0901        | 4.0   | 4776  | 1.0547          |
  | 1.0309        | 5.0   | 5970  | 0.9953          |
  | 0.9842        | 6.0   | 7164  | 0.9997          |
  | 0.9396        | 7.0   | 8358  | 0.9707          |
  | 0.8997        | 8.0   | 9552  | 0.9324          |
  | 0.8633        | 9.0   | 10746 | 0.9145          |
  | 0.8314        | 10.0  | 11940 | 0.9047          |
  | 0.812         | 11.0  | 13134 | 0.8954          |
  | 0.7841        | 12.0  | 14328 | 0.8940          |
  | 0.7616        | 13.0  | 15522 | 0.8555          |
  | 0.7508        | 14.0  | 16716 | 0.8711          |
  | 0.7333        | 15.0  | 17910 | 0.8351          |
  | 0.7299        | 16.0  | 19104 | 0.8646          |
  
  
  ### Framework versions
  
  - Transformers 4.21.2
  - Pytorch 1.12.1+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  