---
license: mit
base_model: cahya/bert-base-indonesian-NER
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: ner_fine_tuned
  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. -->

# ner_fine_tuned

This model is a fine-tuned version of [cahya/bert-base-indonesian-NER](https://huggingface.co/cahya/bert-base-indonesian-NER) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0080
- Precision: 0.6970
- Recall: 0.5349
- F1: 0.6053
- Accuracy: 0.8900

## 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: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 8    | 0.5649          | 0.625     | 0.4651 | 0.5333 | 0.8832   |
| No log        | 2.0   | 16   | 0.6457          | 0.7857    | 0.5116 | 0.6197 | 0.9003   |
| No log        | 3.0   | 24   | 0.7181          | 0.6471    | 0.5116 | 0.5714 | 0.8832   |
| No log        | 4.0   | 32   | 0.8134          | 0.6970    | 0.5349 | 0.6053 | 0.8900   |
| No log        | 5.0   | 40   | 0.8528          | 0.6667    | 0.5116 | 0.5789 | 0.8866   |
| No log        | 6.0   | 48   | 0.8893          | 0.6667    | 0.5116 | 0.5789 | 0.8866   |
| No log        | 7.0   | 56   | 0.9148          | 0.6667    | 0.5116 | 0.5789 | 0.8866   |
| No log        | 8.0   | 64   | 0.9440          | 0.6667    | 0.5116 | 0.5789 | 0.8866   |
| No log        | 9.0   | 72   | 0.9744          | 0.6970    | 0.5349 | 0.6053 | 0.8900   |
| No log        | 10.0  | 80   | 0.9895          | 0.6765    | 0.5349 | 0.5974 | 0.8900   |
| No log        | 11.0  | 88   | 0.9968          | 0.6970    | 0.5349 | 0.6053 | 0.8900   |
| No log        | 12.0  | 96   | 1.0015          | 0.6970    | 0.5349 | 0.6053 | 0.8900   |
| No log        | 13.0  | 104  | 1.0049          | 0.6970    | 0.5349 | 0.6053 | 0.8900   |
| No log        | 14.0  | 112  | 1.0072          | 0.6970    | 0.5349 | 0.6053 | 0.8900   |
| No log        | 15.0  | 120  | 1.0080          | 0.6970    | 0.5349 | 0.6053 | 0.8900   |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1