Instructions to use elidle/indobert-post-training-fin-sa-exp-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use elidle/indobert-post-training-fin-sa-exp-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="elidle/indobert-post-training-fin-sa-exp-2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("elidle/indobert-post-training-fin-sa-exp-2") model = AutoModelForSequenceClassification.from_pretrained("elidle/indobert-post-training-fin-sa-exp-2") - Notebooks
- Google Colab
- Kaggle
indobert-post-training-fin-sa-4
This model is a fine-tuned version of elidle/indobert-fin_news-mlm-3 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2555
- Accuracy: 0.9615
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 8
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.0597 | 0.1961 | 10 | 0.6693 | 0.7527 |
| 0.5333 | 0.3922 | 20 | 0.4162 | 0.8187 |
| 0.3855 | 0.5882 | 30 | 0.2527 | 0.9176 |
| 0.2547 | 0.7843 | 40 | 0.2264 | 0.9341 |
| 0.1848 | 0.9804 | 50 | 0.2274 | 0.9231 |
| 0.1865 | 1.1765 | 60 | 0.1852 | 0.9451 |
| 0.1104 | 1.3725 | 70 | 0.1674 | 0.9615 |
| 0.0857 | 1.5686 | 80 | 0.1744 | 0.9505 |
| 0.123 | 1.7647 | 90 | 0.1966 | 0.9451 |
| 0.1361 | 1.9608 | 100 | 0.1715 | 0.9451 |
| 0.0433 | 2.1569 | 110 | 0.1485 | 0.9670 |
| 0.0244 | 2.3529 | 120 | 0.1727 | 0.9615 |
| 0.0542 | 2.5490 | 130 | 0.2046 | 0.9560 |
| 0.0673 | 2.7451 | 140 | 0.3079 | 0.9396 |
| 0.0993 | 2.9412 | 150 | 0.2305 | 0.9560 |
| 0.0052 | 3.1373 | 160 | 0.2376 | 0.9560 |
| 0.0678 | 3.3333 | 170 | 0.2565 | 0.9615 |
| 0.0095 | 3.5294 | 180 | 0.2565 | 0.9560 |
| 0.0233 | 3.7255 | 190 | 0.2555 | 0.9615 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1
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Model tree for elidle/indobert-post-training-fin-sa-exp-2
Base model
indobenchmark/indobert-base-p1 Finetuned
elidle/indobert-fin_news-mlm