---
base_model: klue/roberta-large
tags:
- generated_from_trainer
datasets:
- klue
model-index:
- name: sts_roberta_large_lr1e-05_wd1e-03_ep10_ckpt
  results: []
---

<!-- 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. -->

# sts_roberta_large_lr1e-05_wd1e-03_ep10_ckpt

This model is a fine-tuned version of [klue/roberta-large](https://huggingface.co/klue/roberta-large) on the klue dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3764
- Mse: 0.3764
- Mae: 0.4512
- R2: 0.8277

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Mse    | Mae    | R2     |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|
| 2.3411        | 1.0   | 183  | 1.0407          | 1.0407 | 0.7779 | 0.5234 |
| 0.1725        | 2.0   | 366  | 0.3938          | 0.3938 | 0.4710 | 0.8197 |
| 0.1203        | 3.0   | 549  | 0.3972          | 0.3972 | 0.4594 | 0.8181 |
| 0.093         | 4.0   | 732  | 0.4030          | 0.4030 | 0.4675 | 0.8155 |
| 0.0727        | 5.0   | 915  | 0.4102          | 0.4102 | 0.4690 | 0.8122 |
| 0.0591        | 6.0   | 1098 | 0.3700          | 0.3700 | 0.4470 | 0.8306 |
| 0.0482        | 7.0   | 1281 | 0.3578          | 0.3578 | 0.4403 | 0.8362 |
| 0.0417        | 8.0   | 1464 | 0.4042          | 0.4042 | 0.4696 | 0.8149 |
| 0.037         | 9.0   | 1647 | 0.4151          | 0.4151 | 0.4753 | 0.8099 |
| 0.0337        | 10.0  | 1830 | 0.3764          | 0.3764 | 0.4512 | 0.8277 |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1+cu117
- Datasets 2.13.0
- Tokenizers 0.13.3