metadata
license: mit
base_model: indobenchmark/indobert-base-p2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: story_model
results: []
story_model
This model is a fine-tuned version of indobenchmark/indobert-base-p2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2576
- Accuracy: 0.9409
- F1: 0.9622
- Precision: 0.9929
- Recall: 0.9333
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 94 | 0.3243 | 0.8817 | 0.9308 | 0.8810 | 0.9867 |
| No log | 2.0 | 188 | 0.2781 | 0.8925 | 0.9363 | 0.8963 | 0.98 |
| No log | 3.0 | 282 | 0.2576 | 0.9409 | 0.9622 | 0.9929 | 0.9333 |
| No log | 4.0 | 376 | 0.3482 | 0.9247 | 0.9545 | 0.9304 | 0.98 |
| No log | 5.0 | 470 | 0.3785 | 0.9301 | 0.9574 | 0.9419 | 0.9733 |
| 0.1516 | 6.0 | 564 | 0.4252 | 0.9140 | 0.9467 | 0.9467 | 0.9467 |
| 0.1516 | 7.0 | 658 | 0.5097 | 0.9086 | 0.9428 | 0.9524 | 0.9333 |
| 0.1516 | 8.0 | 752 | 0.5036 | 0.9086 | 0.9431 | 0.9463 | 0.94 |
| 0.1516 | 9.0 | 846 | 0.5268 | 0.9086 | 0.9439 | 0.9346 | 0.9533 |
| 0.1516 | 10.0 | 940 | 0.5314 | 0.9086 | 0.9439 | 0.9346 | 0.9533 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0