---
license: mit
base_model: xlm-roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
model-index:
- name: xlmr-large-nli-indoindo
  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. -->

# xlmr-large-nli-indoindo

This model is a fine-tuned version of [xlm-roberta-large](https://huggingface.co/xlm-roberta-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3131
- Accuracy: 0.8584
- Precision: 0.8584
- Recall: 0.8584
- F1 Score: 0.8585

## 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: 3e-06
- train_batch_size: 1
- eval_batch_size: 1
- 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: 6

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Precision | Recall | F1 Score |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:--------:|
| 1.449         | 1.0   | 10330 | 1.2228          | 0.7838   | 0.7838    | 0.7838 | 0.7810   |
| 1.2575        | 2.0   | 20660 | 1.1182          | 0.8257   | 0.8257    | 0.8257 | 0.8273   |
| 0.8123        | 3.0   | 30990 | 1.1538          | 0.8489   | 0.8489    | 0.8489 | 0.8488   |
| 0.6541        | 4.0   | 41320 | 1.1288          | 0.8562   | 0.8562    | 0.8562 | 0.8558   |
| 0.3653        | 5.0   | 51650 | 1.2424          | 0.8543   | 0.8543    | 0.8543 | 0.8544   |
| 0.3436        | 6.0   | 61980 | 1.3131          | 0.8584   | 0.8584    | 0.8584 | 0.8585   |


### Framework versions

- Transformers 4.33.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3