readme: ---
  tags:
  - generated_from_trainer
  datasets:
  - klue
  metrics:
  - pearsonr
  model-index:
  - name: roberta-base-finetuned-sts
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: klue
        type: klue
        args: sts
      metrics:
      - name: Pearsonr
        type: pearsonr
        value: 0.956039443806831
  ---
  
  <!-- 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. -->
  
  # roberta-base-finetuned-sts
  
  This model is a fine-tuned version of [klue/roberta-base](https://huggingface.co/klue/roberta-base) on the klue dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1999
  - Pearsonr: 0.9560
  
  ## 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: 32
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 200
  - num_epochs: 15
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Pearsonr |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | No log        | 1.0   | 329  | 0.2462          | 0.9478   |
  | 1.2505        | 2.0   | 658  | 0.1671          | 0.9530   |
  | 1.2505        | 3.0   | 987  | 0.1890          | 0.9525   |
  | 0.133         | 4.0   | 1316 | 0.2360          | 0.9548   |
  | 0.0886        | 5.0   | 1645 | 0.2265          | 0.9528   |
  | 0.0886        | 6.0   | 1974 | 0.2097          | 0.9518   |
  | 0.0687        | 7.0   | 2303 | 0.2281          | 0.9523   |
  | 0.0539        | 8.0   | 2632 | 0.2212          | 0.9542   |
  | 0.0539        | 9.0   | 2961 | 0.1843          | 0.9532   |
  | 0.045         | 10.0  | 3290 | 0.1999          | 0.9560   |
  | 0.0378        | 11.0  | 3619 | 0.2357          | 0.9533   |
  | 0.0378        | 12.0  | 3948 | 0.2134          | 0.9541   |
  | 0.033         | 13.0  | 4277 | 0.2273          | 0.9540   |
  | 0.03          | 14.0  | 4606 | 0.2148          | 0.9533   |
  | 0.03          | 15.0  | 4935 | 0.2207          | 0.9534   |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.10.0+cu111
  - Datasets 2.0.0
  - Tokenizers 0.11.6
  