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---
base_model: naufalihsan/indonesian-sbert-large
tags:
- generated_from_trainer
datasets:
- indonlu
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: sentiment
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: indonlu
type: indonlu
config: smsa
split: validation
args: smsa
metrics:
- name: Accuracy
type: accuracy
value: 0.95
- name: Precision
type: precision
value: 0.9499758037063356
- name: Recall
type: recall
value: 0.95
- name: F1
type: f1
value: 0.9496487652420723
---
<!-- 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. -->
# sentiment
This model is a fine-tuned version of [naufalihsan/indonesian-sbert-large](https://huggingface.co/naufalihsan/indonesian-sbert-large) on the indonlu dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4450
- Accuracy: 0.95
- Precision: 0.9500
- Recall: 0.95
- F1: 0.9496
## 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: 40
- eval_batch_size: 40
- 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 | 275 | 0.2837 | 0.9405 | 0.9427 | 0.9405 | 0.9396 |
| 0.0501 | 2.0 | 550 | 0.1966 | 0.9460 | 0.9468 | 0.9460 | 0.9458 |
| 0.0501 | 3.0 | 825 | 0.2927 | 0.9437 | 0.9435 | 0.9437 | 0.9427 |
| 0.0369 | 4.0 | 1100 | 0.3666 | 0.9460 | 0.9459 | 0.9460 | 0.9456 |
| 0.0369 | 5.0 | 1375 | 0.3579 | 0.9468 | 0.9465 | 0.9468 | 0.9465 |
| 0.0098 | 6.0 | 1650 | 0.4497 | 0.9476 | 0.9479 | 0.9476 | 0.9471 |
| 0.0098 | 7.0 | 1925 | 0.4308 | 0.95 | 0.9501 | 0.95 | 0.9496 |
| 0.0012 | 8.0 | 2200 | 0.4402 | 0.95 | 0.9499 | 0.95 | 0.9496 |
| 0.0012 | 9.0 | 2475 | 0.4429 | 0.95 | 0.9500 | 0.95 | 0.9496 |
| 0.0007 | 10.0 | 2750 | 0.4450 | 0.95 | 0.9500 | 0.95 | 0.9496 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
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