readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: bert-small-nan-labels-500
    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-small-nan-labels-500
  
  This model is a fine-tuned version of [google/bert_uncased_L-4_H-512_A-8](https://huggingface.co/google/bert_uncased_L-4_H-512_A-8) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 8.1664
  
  ## 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: 500
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss |
  |:-------------:|:-----:|:----:|:---------------:|
  | 4.9422        | 1.0   | 14   | 5.5730          |
  | 4.4976        | 2.0   | 28   | 5.4533          |
  | 4.2684        | 3.0   | 42   | 5.4158          |
  | 4.2673        | 4.0   | 56   | 5.4162          |
  | 4.0978        | 5.0   | 70   | 5.4121          |
  | 3.8972        | 6.0   | 84   | 5.4649          |
  | 3.7728        | 7.0   | 98   | 5.4233          |
  | 3.7557        | 8.0   | 112  | 5.4381          |
  | 3.693         | 9.0   | 126  | 5.4673          |
  | 3.5627        | 10.0  | 140  | 5.5277          |
  | 3.6456        | 11.0  | 154  | 5.4351          |
  | 3.5487        | 12.0  | 168  | 5.4846          |
  | 3.4018        | 13.0  | 182  | 5.5763          |
  | 3.3807        | 14.0  | 196  | 5.5674          |
  | 3.4219        | 15.0  | 210  | 5.6129          |
  | 3.3481        | 16.0  | 224  | 5.5470          |
  | 3.2522        | 17.0  | 238  | 5.6078          |
  | 3.3047        | 18.0  | 252  | 5.6274          |
  | 3.1542        | 19.0  | 266  | 5.6517          |
  | 3.0939        | 20.0  | 280  | 5.6088          |
  | 3.0951        | 21.0  | 294  | 5.6768          |
  | 3.0876        | 22.0  | 308  | 5.6796          |
  | 3.0098        | 23.0  | 322  | 5.6938          |
  | 3.061         | 24.0  | 336  | 5.7355          |
  | 2.8711        | 25.0  | 350  | 5.6882          |
  | 2.7414        | 26.0  | 364  | 5.7694          |
  | 2.8273        | 27.0  | 378  | 5.7295          |
  | 2.8497        | 28.0  | 392  | 5.7976          |
  | 2.8469        | 29.0  | 406  | 5.7935          |
  | 2.8367        | 30.0  | 420  | 5.8076          |
  | 2.6975        | 31.0  | 434  | 5.7854          |
  | 2.7496        | 32.0  | 448  | 5.8664          |
  | 2.638         | 33.0  | 462  | 5.8900          |
  | 2.6511        | 34.0  | 476  | 5.8628          |
  | 2.6228        | 35.0  | 490  | 5.8544          |
  | 2.617         | 36.0  | 504  | 5.8830          |
  | 2.498         | 37.0  | 518  | 5.9080          |
  | 2.4956        | 38.0  | 532  | 6.0102          |
  | 2.445         | 39.0  | 546  | 5.9869          |
  | 2.4493        | 40.0  | 560  | 6.0824          |
  | 2.3935        | 41.0  | 574  | 5.9724          |
  | 2.3559        | 42.0  | 588  | 5.9515          |
  | 2.3444        | 43.0  | 602  | 5.9968          |
  | 2.2707        | 44.0  | 616  | 6.0433          |
  | 2.1095        | 45.0  | 630  | 6.0700          |
  | 2.1573        | 46.0  | 644  | 6.1757          |
  | 2.2504        | 47.0  | 658  | 6.0801          |
  | 2.25          | 48.0  | 672  | 6.1659          |
  | 2.1047        | 49.0  | 686  | 6.1564          |
  | 2.1563        | 50.0  | 700  | 6.2225          |
  | 2.0882        | 51.0  | 714  | 6.2024          |
  | 2.1818        | 52.0  | 728  | 6.1418          |
  | 2.1141        | 53.0  | 742  | 6.2118          |
  | 2.0647        | 54.0  | 756  | 6.2645          |
  | 1.9779        | 55.0  | 770  | 6.3598          |
  | 2.053         | 56.0  | 784  | 6.2241          |
  | 1.9884        | 57.0  | 798  | 6.2838          |
  | 1.8604        | 58.0  | 812  | 6.3798          |
  | 1.882         | 59.0  | 826  | 6.3210          |
  | 1.9414        | 60.0  | 840  | 6.3404          |
  | 1.7435        | 61.0  | 854  | 6.3332          |
  | 1.8813        | 62.0  | 868  | 6.3616          |
  | 1.7517        | 63.0  | 882  | 6.4093          |
  | 1.8046        | 64.0  | 896  | 6.4665          |
  | 1.7258        | 65.0  | 910  | 6.4227          |
  | 1.7862        | 66.0  | 924  | 6.3705          |
  | 1.5828        | 67.0  | 938  | 6.5138          |
  | 1.7249        | 68.0  | 952  | 6.4484          |
  | 1.692         | 69.0  | 966  | 6.4739          |
  | 1.575         | 70.0  | 980  | 6.4886          |
  | 1.6542        | 71.0  | 994  | 6.4457          |
  | 1.515         | 72.0  | 1008 | 6.5828          |
  | 1.6127        | 73.0  | 1022 | 6.5665          |
  | 1.6343        | 74.0  | 1036 | 6.5662          |
  | 1.4653        | 75.0  | 1050 | 6.5909          |
  | 1.5358        | 76.0  | 1064 