readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: bert-base-uncased-finetuned-classification
    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
  
  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: 38.9115
  - Mse: 38.9115
  - Mae: 4.5330
  - R2: 0.7802
  - Accuracy: 0.1620
  - Msev: 0.0257
  
  ## 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   |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:------:|:--------:|:------:|
  | 12.4524       | 1.0   | 5215  | 43.9797         | 43.9797 | 4.8194 | 0.7515 | 0.1693   | 0.0227 |
  | 4.393         | 2.0   | 10430 | 39.2333         | 39.2333 | 4.6028 | 0.7783 | 0.1737   | 0.0255 |
  | 2.424         | 3.0   | 15645 | 41.3763         | 41.3763 | 4.6597 | 0.7662 | 0.1620   | 0.0242 |
  | 1.781         | 4.0   | 20860 | 39.4309         | 39.4309 | 4.5960 | 0.7772 | 0.1767   | 0.0254 |
  | 1.3608        | 5.0   | 26075 | 38.9115         | 38.9115 | 4.5330 | 0.7802 | 0.1620   | 0.0257 |
  | 1.2014        | 6.0   | 31290 | 39.7403         | 39.7403 | 4.5850 | 0.7755 | 0.1716   | 0.0252 |
  | 1.0742        | 7.0   | 36505 | 40.4495         | 40.4495 | 4.6133 | 0.7715 | 0.1685   | 0.0247 |
  | 0.837         | 8.0   | 41720 | 39.5864         | 39.5864 | 4.5630 | 0.7763 | 0.1620   | 0.0253 |
  | 0.8054        | 9.0   | 46935 | 39.9482         | 39.9482 | 4.5839 | 0.7743 | 0.1569   | 0.0250 |
  | 0.8085        | 10.0  | 52150 | 39.5685         | 39.5685 | 4.5669 | 0.7764 | 0.1573   | 0.0253 |
  
  
  ### Framework versions
  
  - Transformers 4.21.3
  - Pytorch 1.12.1+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  