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---
license: mit
base_model: cahya/bert-base-indonesian-NER
tags:
- generated_from_trainer
datasets:
- indonlu_nergrit
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: belajarner
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: indonlu_nergrit
type: indonlu_nergrit
config: indonlu_nergrit_source
split: validation
args: indonlu_nergrit_source
metrics:
- name: Precision
type: precision
value: 0.7716312056737589
- name: Recall
type: recall
value: 0.8217522658610272
- name: F1
type: f1
value: 0.7959034381858083
- name: Accuracy
type: accuracy
value: 0.9477048970719857
---
<!-- 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. -->
# belajarner
This model is a fine-tuned version of [cahya/bert-base-indonesian-NER](https://huggingface.co/cahya/bert-base-indonesian-NER) on the indonlu_nergrit dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2621
- Precision: 0.7716
- Recall: 0.8218
- F1: 0.7959
- Accuracy: 0.9477
## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 1.0 | 209 | 0.1633 | 0.7678 | 0.8142 | 0.7903 | 0.9476 |
| No log | 2.0 | 418 | 0.1623 | 0.7631 | 0.8127 | 0.7871 | 0.9462 |
| 0.1633 | 3.0 | 627 | 0.1978 | 0.7535 | 0.8172 | 0.7841 | 0.9459 |
| 0.1633 | 4.0 | 836 | 0.2103 | 0.7573 | 0.8202 | 0.7875 | 0.9460 |
| 0.0423 | 5.0 | 1045 | 0.2236 | 0.7757 | 0.8097 | 0.7923 | 0.9487 |
| 0.0423 | 6.0 | 1254 | 0.2529 | 0.7843 | 0.8293 | 0.8062 | 0.9474 |
| 0.0423 | 7.0 | 1463 | 0.2559 | 0.77 | 0.8142 | 0.7915 | 0.9467 |
| 0.0136 | 8.0 | 1672 | 0.2621 | 0.7716 | 0.8218 | 0.7959 | 0.9477 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2
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