readme: ---
  license: cc-by-sa-4.0
  tags:
  - generated_from_trainer
  datasets:
  - klue
  metrics:
  - pearsonr
  model-index:
  - name: bert-base-finetuned-sts-v3
    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: 0.9172194083849969
  ---
  
  <!-- 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-v3
  
  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: 0.3716
  - Pearsonr: 0.9172
  
  ## 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: 20
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Pearsonr |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
  | 0.2265        | 1.0   | 2917  | 0.4886          | 0.8933   |
  | 0.1504        | 2.0   | 5834  | 0.4374          | 0.8948   |
  | 0.0982        | 3.0   | 8751  | 0.5246          | 0.8957   |
  | 0.0832        | 4.0   | 11668 | 0.4387          | 0.9006   |
  | 0.0751        | 5.0   | 14585 | 0.4036          | 0.9049   |
  | 0.0564        | 6.0   | 17502 | 0.3828          | 0.9133   |
  | 0.0488        | 7.0   | 20419 | 0.3716          | 0.9172   |
  | 0.0384        | 8.0   | 23336 | 0.4060          | 0.9093   |
  | 0.0365        | 9.0   | 26253 | 0.3939          | 0.9065   |
  | 0.0319        | 10.0  | 29170 | 0.3953          | 0.9106   |
  | 0.0262        | 11.0  | 32087 | 0.3885          | 0.9109   |
  | 0.0219        | 12.0  | 35004 | 0.3724          | 0.9154   |
  | 0.0188        | 13.0  | 37921 | 0.3827          | 0.9111   |
  | 0.0175        | 14.0  | 40838 | 0.4103          | 0.9099   |
  | 0.0144        | 15.0  | 43755 | 0.3768          | 0.9152   |
  | 0.0132        | 16.0  | 46672 | 0.3868          | 0.9151   |
  | 0.0125        | 17.0  | 49589 | 0.3981          | 0.9103   |
  | 0.0106        | 18.0  | 52506 | 0.3808          | 0.9138   |
  | 0.0095        | 19.0  | 55423 | 0.3904          | 0.9128   |
  | 0.0089        | 20.0  | 58340 | 0.3885          | 0.9137   |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.0
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  