---
base_model: ys7yoo/nli_roberta-large_lr1e-05_wd1e-03_ep3
tags:
- generated_from_trainer
datasets:
- klue
model-index:
- name: sts_nli_roberta-large_lr1e-05_wd1e-03_ep3_lr1e-05_wd1e-03_ep9_ckpt
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# sts_nli_roberta-large_lr1e-05_wd1e-03_ep3_lr1e-05_wd1e-03_ep9_ckpt

This model is a fine-tuned version of [ys7yoo/nli_roberta-large_lr1e-05_wd1e-03_ep3](https://huggingface.co/ys7yoo/nli_roberta-large_lr1e-05_wd1e-03_ep3) on the klue dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3250
- Mse: 0.3250
- Mae: 0.4166
- R2: 0.8512

## 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: 9

### Training results

| Training Loss | Epoch | Step | Validation Loss | Mse    | Mae    | R2     |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|
| 1.2084        | 1.0   | 183  | 0.5071          | 0.5071 | 0.5306 | 0.7678 |
| 0.1515        | 2.0   | 366  | 0.3142          | 0.3142 | 0.4149 | 0.8561 |
| 0.103         | 3.0   | 549  | 0.3284          | 0.3284 | 0.4150 | 0.8496 |
| 0.0779        | 4.0   | 732  | 0.3306          | 0.3306 | 0.4184 | 0.8486 |
| 0.0597        | 5.0   | 915  | 0.3219          | 0.3219 | 0.4098 | 0.8526 |
| 0.0497        | 6.0   | 1098 | 0.3324          | 0.3324 | 0.4175 | 0.8478 |
| 0.0407        | 7.0   | 1281 | 0.3114          | 0.3114 | 0.4119 | 0.8574 |
| 0.0356        | 8.0   | 1464 | 0.3305          | 0.3305 | 0.4199 | 0.8486 |
| 0.0327        | 9.0   | 1647 | 0.3250          | 0.3250 | 0.4166 | 0.8512 |


### Framework versions

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