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---
license: mit
base_model: indobenchmark/indobart
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: bdc2024-indobert-filtered-1
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. -->
# bdc2024-indobert-filtered-1
This model is a fine-tuned version of [indobenchmark/indobart](https://huggingface.co/indobenchmark/indobart) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5705
- Accuracy: 0.8317
- Balanced Accuracy: 0.6247
- Precision: 0.8316
- Recall: 0.8317
- F1: 0.8173
## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Balanced Accuracy | Precision | Recall | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------------:|:---------:|:------:|:------:|
| No log | 1.0 | 298 | 0.9280 | 0.6998 | 0.3859 | 0.6874 | 0.6998 | 0.6350 |
| 0.886 | 2.0 | 596 | 0.7598 | 0.7648 | 0.4862 | 0.7263 | 0.7648 | 0.7251 |
| 0.886 | 3.0 | 894 | 0.6400 | 0.7992 | 0.5757 | 0.8018 | 0.7992 | 0.7772 |
| 0.5453 | 4.0 | 1192 | 0.5738 | 0.8298 | 0.6337 | 0.8321 | 0.8298 | 0.8184 |
| 0.5453 | 5.0 | 1490 | 0.5705 | 0.8317 | 0.6247 | 0.8316 | 0.8317 | 0.8173 |
### Framework versions
- Transformers 4.33.1
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.13.3
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