---
base_model: klue/roberta-large
tags:
- generated_from_trainer
datasets:
- klue
metrics:
- accuracy
- f1
model-index:
- name: nli_roberta-large_lr1e-05_wd1e-03_ep3_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: 0.9026666666666666
    - name: F1
      type: f1
      value: 0.9025716877431428
---

<!-- 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_roberta-large_lr1e-05_wd1e-03_ep3_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: 0.3425
- Accuracy: 0.9027
- F1: 0.9026

## 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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.5725        | 1.0   | 391  | 0.3381          | 0.8813   | 0.8811 |
| 0.2182        | 2.0   | 782  | 0.3055          | 0.898    | 0.8979 |
| 0.112         | 3.0   | 1173 | 0.3425          | 0.9027   | 0.9026 |


### Framework versions

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