---
base_model: ys7yoo/nli_klue_roberta_large_ep9
tags:
- generated_from_trainer
datasets:
- klue
model-index:
- name: sts_ys7yoo_nli_klue_roberta_large_ep9_ep9
  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_ys7yoo_nli_klue_roberta_large_ep9_ep9

This model is a fine-tuned version of [ys7yoo/nli_klue_roberta_large_ep9](https://huggingface.co/ys7yoo/nli_klue_roberta_large_ep9) on the klue dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3322
- Mse: 0.3322
- Mae: 0.4242
- R2: 0.8479

## 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: 5e-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: 9

### Training results

| Training Loss | Epoch | Step | Validation Loss | Mse    | Mae    | R2     |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|
| 1.1881        | 1.0   | 183  | 0.4082          | 0.4082 | 0.4975 | 0.8131 |
| 0.1751        | 2.0   | 366  | 0.4353          | 0.4353 | 0.4964 | 0.8007 |
| 0.1222        | 3.0   | 549  | 0.3238          | 0.3238 | 0.4144 | 0.8517 |
| 0.0899        | 4.0   | 732  | 0.3434          | 0.3434 | 0.4482 | 0.8428 |
| 0.0659        | 5.0   | 915  | 0.3174          | 0.3174 | 0.4191 | 0.8547 |
| 0.0483        | 6.0   | 1098 | 0.3439          | 0.3439 | 0.4422 | 0.8425 |
| 0.0361        | 7.0   | 1281 | 0.3472          | 0.3472 | 0.4402 | 0.8410 |
| 0.0265        | 8.0   | 1464 | 0.3667          | 0.3667 | 0.4426 | 0.8321 |
| 0.0203        | 9.0   | 1647 | 0.3322          | 0.3322 | 0.4242 | 0.8479 |


### Framework versions

- Transformers 4.33.1
- Pytorch 2.0.1+cu117
- Datasets 2.13.0
- Tokenizers 0.13.3