---
base_model: ys7yoo/sts_roberta_large_lr1e-05_wd1e-03_ep10
tags:
- generated_from_trainer
datasets:
- klue
metrics:
- accuracy
- f1
model-index:
- name: nli_sts_roberta_large_lr1e-05_wd1e-03_ep10_lr1e-05_wd1e-03_ep10_ckpt
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: klue
      type: klue
      config: nli
      split: validation
      args: nli
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8963333333333333
    - name: F1
      type: f1
      value: 0.8962457758881018
---

<!-- 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. -->

# nli_sts_roberta_large_lr1e-05_wd1e-03_ep10_lr1e-05_wd1e-03_ep10_ckpt

This model is a fine-tuned version of [ys7yoo/sts_roberta_large_lr1e-05_wd1e-03_ep10](https://huggingface.co/ys7yoo/sts_roberta_large_lr1e-05_wd1e-03_ep10) on the klue dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6903
- Accuracy: 0.8963
- F1: 0.8962

## 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 | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.6445        | 1.0   | 391  | 0.4254          | 0.852    | 0.8512 |
| 0.2943        | 2.0   | 782  | 0.3371          | 0.889    | 0.8886 |
| 0.1586        | 3.0   | 1173 | 0.3704          | 0.888    | 0.8881 |
| 0.0921        | 4.0   | 1564 | 0.4429          | 0.892    | 0.8919 |
| 0.0565        | 5.0   | 1955 | 0.4864          | 0.899    | 0.8989 |
| 0.0378        | 6.0   | 2346 | 0.5727          | 0.8963   | 0.8962 |
| 0.0238        | 7.0   | 2737 | 0.6247          | 0.8957   | 0.8955 |
| 0.016         | 8.0   | 3128 | 0.6578          | 0.8947   | 0.8945 |
| 0.0101        | 9.0   | 3519 | 0.6780          | 0.8953   | 0.8952 |
| 0.0067        | 10.0  | 3910 | 0.6903          | 0.8963   | 0.8962 |


### Framework versions

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