---
language:
- id
license: mit
base_model: indolem/indobert-base-uncased
tags:
- generated_from_trainer
model-index:
- name: nerui-base-0
  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. -->

# nerui-base-0

This model is a fine-tuned version of [indolem/indobert-base-uncased](https://huggingface.co/indolem/indobert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0540
- Location Precision: 0.8544
- Location Recall: 0.9362
- Location F1: 0.8934
- Location Number: 94
- Organization Precision: 0.9119
- Organization Recall: 0.8683
- Organization F1: 0.8896
- Organization Number: 167
- Person Precision: 0.9926
- Person Recall: 0.9781
- Person F1: 0.9853
- Person Number: 137
- Overall Precision: 0.9244
- Overall Recall: 0.9221
- Overall F1: 0.9233
- Overall Accuracy: 0.9851

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Location Precision | Location Recall | Location F1 | Location Number | Organization Precision | Organization Recall | Organization F1 | Organization Number | Person Precision | Person Recall | Person F1 | Person Number | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------------------:|:---------------:|:-----------:|:---------------:|:----------------------:|:-------------------:|:---------------:|:-------------------:|:----------------:|:-------------:|:---------:|:-------------:|:-----------------:|:--------------:|:----------:|:----------------:|
| 0.2529        | 1.0   | 96   | 0.0478          | 0.9438             | 0.8936          | 0.9180      | 94              | 0.8556                 | 0.9222              | 0.8876          | 167                 | 0.9776           | 0.9562        | 0.9668    | 137           | 0.9156            | 0.9271         | 0.9213     | 0.9851           |
| 0.0617        | 2.0   | 192  | 0.0545          | 0.87               | 0.9255          | 0.8969      | 94              | 0.88                   | 0.9222              | 0.9006          | 167                 | 0.9571           | 0.9781        | 0.9675    | 137           | 0.9036            | 0.9422         | 0.9225     | 0.9815           |
| 0.0309        | 3.0   | 288  | 0.0539          | 0.8447             | 0.9255          | 0.8832      | 94              | 0.8868                 | 0.8443              | 0.8650          | 167                 | 0.9708           | 0.9708        | 0.9708    | 137           | 0.9048            | 0.9070         | 0.9059     | 0.9829           |
| 0.0178        | 4.0   | 384  | 0.0556          | 0.8878             | 0.9255          | 0.9062      | 94              | 0.8941                 | 0.9102              | 0.9021          | 167                 | 0.9853           | 0.9781        | 0.9817    | 137           | 0.9233            | 0.9372         | 0.9302     | 0.9845           |
| 0.0103        | 5.0   | 480  | 0.0540          | 0.8544             | 0.9362          | 0.8934      | 94              | 0.9119                 | 0.8683              | 0.8896          | 167                 | 0.9926           | 0.9781        | 0.9853    | 137           | 0.9244            | 0.9221         | 0.9233     | 0.9851           |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.15.2