---
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