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---
license: mit
base_model: LazarusNLP/NusaBERT-base
tags:
- generated_from_trainer
datasets:
- indonlu
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: NusaBERT-base-POSP
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: indonlu
type: indonlu
config: posp
split: validation
args: posp
metrics:
- name: Precision
type: precision
value: 0.9577443609022557
- name: Recall
type: recall
value: 0.9577443609022557
- name: F1
type: f1
value: 0.9577443609022557
- name: Accuracy
type: accuracy
value: 0.9577443609022557
---
<!-- 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. -->
# NusaBERT-base-POSP
This model is a fine-tuned version of [LazarusNLP/NusaBERT-base](https://huggingface.co./LazarusNLP/NusaBERT-base) on the indonlu dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1472
- Precision: 0.9577
- Recall: 0.9577
- F1: 0.9577
- Accuracy: 0.9577
## 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: 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: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 1.0 | 420 | 0.2680 | 0.9203 | 0.9203 | 0.9203 | 0.9203 |
| 0.6283 | 2.0 | 840 | 0.2017 | 0.9379 | 0.9379 | 0.9379 | 0.9379 |
| 0.218 | 3.0 | 1260 | 0.1785 | 0.9449 | 0.9449 | 0.9449 | 0.9449 |
| 0.1612 | 4.0 | 1680 | 0.1692 | 0.9490 | 0.9490 | 0.9490 | 0.9490 |
| 0.1393 | 5.0 | 2100 | 0.1577 | 0.9511 | 0.9511 | 0.9511 | 0.9511 |
| 0.1119 | 6.0 | 2520 | 0.1503 | 0.9539 | 0.9539 | 0.9539 | 0.9539 |
| 0.1119 | 7.0 | 2940 | 0.1499 | 0.9549 | 0.9549 | 0.9549 | 0.9549 |
| 0.0943 | 8.0 | 3360 | 0.1542 | 0.9547 | 0.9547 | 0.9547 | 0.9547 |
| 0.0824 | 9.0 | 3780 | 0.1517 | 0.9558 | 0.9558 | 0.9558 | 0.9558 |
| 0.0785 | 10.0 | 4200 | 0.1519 | 0.9557 | 0.9557 | 0.9557 | 0.9557 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu118
- Datasets 2.17.1
- Tokenizers 0.15.1
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