---
license: mit
base_model: indobenchmark/indobert-base-p1
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: indobert-base-p1-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-p1-reddit-indonesia-sarcastic

This model is a fine-tuned version of [indobenchmark/indobert-base-p1](https://huggingface.co/indobenchmark/indobert-base-p1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4390
- Accuracy: 0.7921
- F1: 0.6100
- Precision: 0.5745
- Recall: 0.6501

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.4385        | 1.0   | 309  | 0.4258          | 0.7980   | 0.5675 | 0.6111    | 0.5297 |
| 0.3451        | 2.0   | 618  | 0.4345          | 0.8030   | 0.6283 | 0.5949    | 0.6657 |
| 0.2404        | 3.0   | 927  | 0.5054          | 0.8016   | 0.5318 | 0.6490    | 0.4504 |
| 0.1326        | 4.0   | 1236 | 0.7033          | 0.7860   | 0.5452 | 0.5820    | 0.5127 |
| 0.0787        | 5.0   | 1545 | 0.9796          | 0.7881   | 0.5335 | 0.5938    | 0.4844 |


### Framework versions

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