readme: ---
  license: cc-by-sa-4.0
  tags:
  - generated_from_trainer
  datasets:
  - klue
  metrics:
  - pearsonr
  model-index:
  - name: bert-base-finetuned-sts
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: klue
        type: klue
        config: sts
        split: train
        args: sts
      metrics:
      - name: Pearsonr
        type: pearsonr
        value: 0.9116408161709073
  ---
  
  <!-- 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-finetuned-sts
  
  This model is a fine-tuned version of [klue/bert-base](https://huggingface.co/klue/bert-base) on the klue dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3951
  - Pearsonr: 0.9116
  
  ## 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: 2e-05
  - train_batch_size: 4
  - eval_batch_size: 4
  - 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 | Pearsonr |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
  | 0.2345        | 1.0   | 2917  | 0.7037          | 0.8757   |
  | 0.1491        | 2.0   | 5834  | 0.4869          | 0.8846   |
  | 0.097         | 3.0   | 8751  | 0.4023          | 0.9041   |
  | 0.0735        | 4.0   | 11668 | 0.3960          | 0.9073   |
  | 0.0644        | 5.0   | 14585 | 0.4838          | 0.8989   |
  | 0.0446        | 6.0   | 17502 | 0.3990          | 0.9078   |
  | 0.0355        | 7.0   | 20419 | 0.3951          | 0.9116   |
  | 0.0277        | 8.0   | 23336 | 0.4284          | 0.9053   |
  | 0.0239        | 9.0   | 26253 | 0.4166          | 0.9073   |
  | 0.0205        | 10.0  | 29170 | 0.4234          | 0.9062   |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.0
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  