---
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: xlm-roberta-base-twitter-indonesia-sarcastic
  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. -->

# xlm-roberta-base-twitter-indonesia-sarcastic

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4359
- Accuracy: 0.8513
- F1: 0.7386
- Precision: 0.6570
- Recall: 0.8433

## 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: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 100.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.5641        | 1.0   | 59   | 0.5260          | 0.75     | 0.0    | 0.0       | 0.0    |
| 0.5317        | 2.0   | 118  | 0.5030          | 0.75     | 0.0    | 0.0       | 0.0    |
| 0.4995        | 3.0   | 177  | 0.4656          | 0.75     | 0.0    | 0.0       | 0.0    |
| 0.4599        | 4.0   | 236  | 0.4503          | 0.7687   | 0.6026 | 0.5281    | 0.7015 |
| 0.4082        | 5.0   | 295  | 0.3785          | 0.8470   | 0.6435 | 0.7708    | 0.5522 |
| 0.3274        | 6.0   | 354  | 0.3605          | 0.8619   | 0.6992 | 0.7679    | 0.6418 |
| 0.2621        | 7.0   | 413  | 0.3765          | 0.8619   | 0.6838 | 0.8       | 0.5970 |
| 0.2332        | 8.0   | 472  | 0.3408          | 0.8769   | 0.7591 | 0.7429    | 0.7761 |
| 0.1579        | 9.0   | 531  | 0.4382          | 0.8731   | 0.7213 | 0.8       | 0.6567 |
| 0.1467        | 10.0  | 590  | 0.3855          | 0.8806   | 0.7895 | 0.7059    | 0.8955 |
| 0.098         | 11.0  | 649  | 0.4693          | 0.8806   | 0.7500 | 0.7869    | 0.7164 |
| 0.0929        | 12.0  | 708  | 0.6206          | 0.8806   | 0.7333 | 0.8302    | 0.6567 |
| 0.0555        | 13.0  | 767  | 0.7134          | 0.8843   | 0.7634 | 0.7812    | 0.7463 |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0