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---
library_name: transformers
license: mit
base_model: indobenchmark/indobert-large-p1
tags:
- generated_from_trainer
metrics:
- precision
- f1
model-index:
- name: indobert-smsa_doc-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. -->
# indobert-smsa_doc-finetuned
This model is a fine-tuned version of [indobenchmark/indobert-large-p1](https://huggingface.co/indobenchmark/indobert-large-p1) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3324
- Precision: 0.9413
- F1: 0.9413
## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | F1 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
| 0.0285 | 1.0 | 1238 | 0.2476 | 0.9357 | 0.9357 |
| 0.0076 | 2.0 | 2476 | 0.2532 | 0.9397 | 0.9397 |
| 0.001 | 3.0 | 3714 | 0.3324 | 0.9413 | 0.9413 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1
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