transformers pytorch roberta text-classification generated_from_trainer dataset:klue base_model:ys7yoo/sts_roberta-large_lr1e-05_wd1e-03_ep5 base_model:finetune:ys7yoo/sts_roberta-large_lr1e-05_wd1e-03_ep5 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: ys7yoo/sts_roberta_large_lr1e-05_wd1e-03_ep5
datasets:
- klue
metrics:
- accuracy
- f1
tags:
- generated_from_trainer
model-index:
- name: nli_sts_roberta_large_lr1e_05_wd1e_03_ep5_lr1e-05_wd1e-03_ep5_ckpt
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: klue
      type: klue
      config: nli
      split: validation
      args: nli
    metrics:
    - type: accuracy
      value: 0.8986666666666666
      name: Accuracy
    - type: f1
      value: 0.8985280502079203
      name: F1
---

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# nli_sts_roberta_large_lr1e_05_wd1e_03_ep5_lr1e-05_wd1e-03_ep5_ckpt

This model is a fine-tuned version of [ys7yoo/sts_roberta_large_lr1e-05_wd1e-03_ep5](https://huggingface.co/ys7yoo/sts_roberta_large_lr1e-05_wd1e-03_ep5) on the klue dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4971
- Accuracy: 0.8987
- F1: 0.8985

## 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.5471        | 1.0   | 391  | 0.3522          | 0.876    | 0.8756 |
| 0.2379        | 2.0   | 782  | 0.3345          | 0.8983   | 0.8981 |
| 0.1215        | 3.0   | 1173 | 0.3708          | 0.8997   | 0.8995 |
| 0.0661        | 4.0   | 1564 | 0.4734          | 0.896    | 0.8958 |
| 0.0407        | 5.0   | 1955 | 0.4971          | 0.8987   | 0.8985 |


### Framework versions

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