---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
base_model: xlm-roberta-large
model-index:
- name: fine-tuned-NLI-indonesian-with-xlm-roberta-large
  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. -->

# fine-tuned-NLI-indonesian-with-xlm-roberta-large

This model is a fine-tuned version of [xlm-roberta-large](https://huggingface.co/xlm-roberta-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2112
- Accuracy: 0.9463
- F1: 0.9463

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.7348        | 0.49  | 72   | 0.6119          | 0.6584   | 0.6544 |
| 0.5955        | 0.99  | 144  | 0.2496          | 0.8959   | 0.8959 |
| 0.2352        | 1.49  | 216  | 0.1968          | 0.9169   | 0.9169 |
| 0.1987        | 1.98  | 288  | 0.1773          | 0.9267   | 0.9265 |
| 0.1315        | 2.48  | 360  | 0.1585          | 0.9437   | 0.9437 |
| 0.1206        | 2.97  | 432  | 0.1540          | 0.9411   | 0.9411 |
| 0.0821        | 3.47  | 504  | 0.1861          | 0.9470   | 0.9470 |
| 0.0782        | 3.97  | 576  | 0.1791          | 0.9503   | 0.9503 |
| 0.0743        | 4.47  | 648  | 0.1801          | 0.9476   | 0.9476 |
| 0.0691        | 4.96  | 720  | 0.1902          | 0.9463   | 0.9463 |
| 0.0569        | 5.46  | 792  | 0.2112          | 0.9463   | 0.9463 |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu117
- Datasets 2.2.0
- Tokenizers 0.13.2