readme: ---
  license: cc-by-4.0
  tags:
  - generated_from_trainer
  model-index:
  - name: nb-bert-base-ctr-regression
    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. -->
  
  # nb-bert-base-ctr-regression
  
  This model is a fine-tuned version of [NbAiLab/nb-bert-base](https://huggingface.co/NbAiLab/nb-bert-base) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0073
  - Mse: 0.0073
  
  ## 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: 16
  - eval_batch_size: 64
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - num_epochs: 10
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Mse    |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|
  | 0.0106        | 1.0   | 1103  | 0.0069          | 0.0069 |
  | 0.0073        | 2.0   | 2206  | 0.0072          | 0.0072 |
  | 0.0058        | 3.0   | 3309  | 0.0063          | 0.0063 |
  | 0.0038        | 4.0   | 4412  | 0.0073          | 0.0073 |
  | 0.0025        | 5.0   | 5515  | 0.0064          | 0.0064 |
  | 0.0019        | 6.0   | 6618  | 0.0065          | 0.0065 |
  | 0.0014        | 7.0   | 7721  | 0.0066          | 0.0066 |
  | 0.0011        | 8.0   | 8824  | 0.0067          | 0.0067 |
  | 0.0008        | 9.0   | 9927  | 0.0066          | 0.0066 |
  | 0.0007        | 10.0  | 11030 | 0.0066          | 0.0066 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.10.2+cu113
  - Datasets 1.18.4
  - Tokenizers 0.12.1
  