readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: bert-base-uncased-issues-128
    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-issues-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: 1.2500
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|
  | 2.0975        | 1.0   | 291  | 1.7060          |
  | 1.648         | 2.0   | 582  | 1.4280          |
  | 1.4837        | 3.0   | 873  | 1.3980          |
  | 1.3978        | 4.0   | 1164 | 1.4040          |
  | 1.3314        | 5.0   | 1455 | 1.2032          |
  | 1.2954        | 6.0   | 1746 | 1.2814          |
  | 1.2448        | 7.0   | 2037 | 1.2635          |
  | 1.1983        | 8.0   | 2328 | 1.2071          |
  | 1.1849        | 9.0   | 2619 | 1.1675          |
  | 1.1414        | 10.0  | 2910 | 1.2095          |
  | 1.1314        | 11.0  | 3201 | 1.1858          |
  | 1.0943        | 12.0  | 3492 | 1.1658          |
  | 1.0838        | 13.0  | 3783 | 1.2336          |
  | 1.0733        | 14.0  | 4074 | 1.1606          |
  | 1.0627        | 15.0  | 4365 | 1.1188          |
  | 1.055         | 16.0  | 4656 | 1.2500          |
  
  
  ### Framework versions
  
  - Transformers 4.15.0
  - Pytorch 1.10.0+cu111
  - Datasets 1.17.0
  - Tokenizers 0.10.3
  