transformers safetensors bert text-classification generated_from_trainer base_model:indobenchmark/indobert-base-p1 license:mit autotrain_compatible endpoints_compatible region:us
---
license: mit
base_model: indobenchmark/indobert-base-p1
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: indobert-base-p1-twitter-indonesia-sarcastic
  results: []
---

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# indobert-base-p1-twitter-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: 0.8125
- Accuracy: 0.8662
- F1: 0.7273
- Precision: 0.7385
- Recall: 0.7164

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.5101        | 1.0   | 59   | 0.4221          | 0.7836   | 0.6081 | 0.5556    | 0.6716 |
| 0.3508        | 2.0   | 118  | 0.3479          | 0.8246   | 0.6713 | 0.6316    | 0.7164 |
| 0.221         | 3.0   | 177  | 0.3511          | 0.8582   | 0.6935 | 0.7544    | 0.6418 |
| 0.1157        | 4.0   | 236  | 0.4352          | 0.8396   | 0.6861 | 0.6714    | 0.7015 |
| 0.0453        | 5.0   | 295  | 0.6923          | 0.8582   | 0.7077 | 0.7302    | 0.6866 |
| 0.0192        | 6.0   | 354  | 0.7378          | 0.8694   | 0.7287 | 0.7581    | 0.7015 |
| 0.0159        | 7.0   | 413  | 0.8860          | 0.8545   | 0.6723 | 0.7692    | 0.5970 |
| 0.0165        | 8.0   | 472  | 0.8261          | 0.8694   | 0.7445 | 0.7286    | 0.7612 |
| 0.0175        | 9.0   | 531  | 0.8732          | 0.8731   | 0.7424 | 0.7538    | 0.7313 |
| 0.0062        | 10.0  | 590  | 0.9648          | 0.8657   | 0.7273 | 0.7385    | 0.7164 |
| 0.0003        | 11.0  | 649  | 1.0108          | 0.8619   | 0.7176 | 0.7344    | 0.7015 |


### Framework versions

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