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---
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
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