metadata
library_name: transformers
license: mit
base_model: indolem/indobert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: results
results: []
results
This model is a fine-tuned version of indolem/indobert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0994
- Accuracy: 0.9858
- F1: 0.9850
- Precision: 0.9871
- Recall: 0.9829
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: 3e-05
- train_batch_size: 16
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.1153 | 1.0 | 1478 | 0.0675 | 0.9871 | 0.9865 | 0.9837 | 0.9893 |
| 0.0632 | 2.0 | 2956 | 0.0508 | 0.9882 | 0.9876 | 0.9811 | 0.9943 |
| 0.0397 | 3.0 | 4434 | 0.0546 | 0.9865 | 0.9858 | 0.9810 | 0.9908 |
| 0.027 | 4.0 | 5912 | 0.0817 | 0.9875 | 0.9869 | 0.9858 | 0.9879 |
| 0.0177 | 5.0 | 7390 | 0.0994 | 0.9858 | 0.9850 | 0.9871 | 0.9829 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.4.1
- Datasets 2.19.2
- Tokenizers 0.20.1