---
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