readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: bert-base-uncased-finetuned-classification_TokenNew
    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-finetuned-classification_TokenNew
  
  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 41.4553
  - Mse: 41.4553
  - Mae: 4.7280
  - R2: 0.7658
  - Accuracy: 0.1600
  - Msev: 0.0241
  
  ## 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: 1e-05
  - train_batch_size: 16
  - eval_batch_size: 16
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 10
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Mse     | Mae    | R2     | Accuracy | Msev   |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:------:|:--------:|:------:|
  | 10.3178       | 1.0   | 5215  | 41.8852         | 41.8852 | 4.6705 | 0.7634 | 0.1827   | 0.0239 |
  | 3.6731        | 2.0   | 10430 | 45.6101         | 45.6101 | 4.9092 | 0.7423 | 0.1809   | 0.0219 |
  | 2.0891        | 3.0   | 15645 | 42.1319         | 42.1319 | 4.7640 | 0.7620 | 0.1525   | 0.0237 |
  | 1.5213        | 4.0   | 20860 | 42.0646         | 42.0646 | 4.7562 | 0.7623 | 0.1588   | 0.0238 |
  | 1.1904        | 5.0   | 26075 | 42.0155         | 42.0155 | 4.7778 | 0.7626 | 0.1563   | 0.0238 |
  | 1.0127        | 6.0   | 31290 | 41.6389         | 41.6389 | 4.7342 | 0.7647 | 0.1660   | 0.0240 |
  | 0.9218        | 7.0   | 36505 | 40.9860         | 40.9860 | 4.7009 | 0.7684 | 0.1589   | 0.0244 |
  | 0.7466        | 8.0   | 41720 | 40.1809         | 40.1809 | 4.6686 | 0.7730 | 0.1629   | 0.0249 |
  | 0.7264        | 9.0   | 46935 | 40.9795         | 40.9795 | 4.7043 | 0.7685 | 0.1616   | 0.0244 |
  | 0.6968        | 10.0  | 52150 | 41.4553         | 41.4553 | 4.7280 | 0.7658 | 0.1600   | 0.0241 |
  
  
  ### Framework versions
  
  - Transformers 4.21.3
  - Pytorch 1.12.1+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  