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---
license: mit
base_model: indolem/indobert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: indonesian-brand-indoBERT-finetuned
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. -->
# indonesian-brand-indoBERT-finetuned
This model is a fine-tuned version of [indolem/indobert-base-uncased](https://huggingface.co./indolem/indobert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6848
- Accuracy: 0.8601
- Precision: 0.8601
- Recall: 0.8601
- F1: 0.8601
## 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
- lr_scheduler_warmup_ratio: 0.01
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| No log | 1.0 | 304 | 0.4935 | 0.8132 | 0.8132 | 0.8132 | 0.8132 |
| 0.5911 | 2.0 | 608 | 0.4046 | 0.8362 | 0.8362 | 0.8362 | 0.8362 |
| 0.5911 | 3.0 | 912 | 0.4873 | 0.8305 | 0.8305 | 0.8305 | 0.8305 |
| 0.3204 | 4.0 | 1216 | 0.4774 | 0.8560 | 0.8560 | 0.8560 | 0.8560 |
| 0.2154 | 5.0 | 1520 | 0.5759 | 0.8486 | 0.8486 | 0.8486 | 0.8486 |
| 0.2154 | 6.0 | 1824 | 0.6334 | 0.8568 | 0.8568 | 0.8568 | 0.8568 |
| 0.1454 | 7.0 | 2128 | 0.6848 | 0.8601 | 0.8601 | 0.8601 | 0.8601 |
| 0.1454 | 8.0 | 2432 | 0.7325 | 0.8560 | 0.8560 | 0.8560 | 0.8560 |
| 0.0982 | 9.0 | 2736 | 0.7782 | 0.8568 | 0.8568 | 0.8568 | 0.8568 |
| 0.0729 | 10.0 | 3040 | 0.7979 | 0.8584 | 0.8584 | 0.8584 | 0.8584 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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