---
license: mit
base_model: indobenchmark/indobert-large-p1
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: indobert-large-p1-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. -->

# indobert-large-p1-twitter-indonesia-sarcastic

This model is a fine-tuned version of [indobenchmark/indobert-large-p1](https://huggingface.co/indobenchmark/indobert-large-p1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3207
- Accuracy: 0.8643
- F1: 0.7160
- Precision: 0.7480
- Recall: 0.6866

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.5836        | 1.0   | 59   | 0.4153          | 0.8060   | 0.5738 | 0.6364    | 0.5224 |
| 0.3766        | 2.0   | 118  | 0.3353          | 0.8433   | 0.5962 | 0.8378    | 0.4627 |
| 0.2476        | 3.0   | 177  | 0.3114          | 0.8619   | 0.6942 | 0.7778    | 0.6269 |
| 0.1356        | 4.0   | 236  | 0.3279          | 0.8694   | 0.7328 | 0.75      | 0.7164 |
| 0.0536        | 5.0   | 295  | 0.4265          | 0.8582   | 0.7164 | 0.7164    | 0.7164 |
| 0.0157        | 6.0   | 354  | 0.6448          | 0.8619   | 0.6667 | 0.8409    | 0.5522 |
| 0.0076        | 7.0   | 413  | 0.5739          | 0.8619   | 0.7218 | 0.7273    | 0.7164 |


### Framework versions

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