---
license: mit
base_model: indolem/indobert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: indobert-base-uncased-reddit-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-base-uncased-reddit-indonesia-sarcastic

This model is a fine-tuned version of [indolem/indobert-base-uncased](https://huggingface.co/indolem/indobert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5000
- Accuracy: 0.7670
- F1: 0.5671
- Precision: 0.5295
- Recall: 0.6105

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.5121        | 1.0   | 309  | 0.4942          | 0.7378   | 0.4774 | 0.4761    | 0.4788 |
| 0.4513        | 2.0   | 618  | 0.4422          | 0.7952   | 0.4956 | 0.6455    | 0.4023 |
| 0.4078        | 3.0   | 927  | 0.4771          | 0.7980   | 0.4075 | 0.7656    | 0.2776 |
| 0.3686        | 4.0   | 1236 | 0.4755          | 0.8051   | 0.4898 | 0.7097    | 0.3739 |
| 0.3358        | 5.0   | 1545 | 0.4864          | 0.7753   | 0.5768 | 0.5455    | 0.6119 |
| 0.299         | 6.0   | 1854 | 0.5038          | 0.7633   | 0.5729 | 0.5221    | 0.6346 |
| 0.2602        | 7.0   | 2163 | 0.5242          | 0.7888   | 0.5387 | 0.5939    | 0.4929 |
| 0.2184        | 8.0   | 2472 | 0.6153          | 0.7817   | 0.5523 | 0.5672    | 0.5382 |


### Framework versions

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