metadata
license: mit
base_model: indobenchmark/indobert-base-p2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: fitur_model
results: []
fitur_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: 1.3853
- Accuracy: 0.7857
- F1: 0.6904
- Precision: 0.7095
- Recall: 0.6786
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| No log | 0.54 | 50 | 0.6229 | 0.7582 | 0.6537 | 0.6671 | 0.6454 |
| No log | 1.09 | 100 | 0.6750 | 0.7747 | 0.6557 | 0.6912 | 0.6414 |
| No log | 1.63 | 150 | 0.5936 | 0.7802 | 0.7242 | 0.7137 | 0.7421 |
| No log | 2.17 | 200 | 0.7087 | 0.7912 | 0.7312 | 0.7232 | 0.7419 |
| No log | 2.72 | 250 | 0.9279 | 0.7802 | 0.6796 | 0.7007 | 0.6675 |
| No log | 3.26 | 300 | 1.0408 | 0.7747 | 0.6853 | 0.6940 | 0.6788 |
| No log | 3.8 | 350 | 1.2506 | 0.7857 | 0.7007 | 0.7100 | 0.6935 |
| No log | 4.35 | 400 | 1.4011 | 0.7802 | 0.6796 | 0.7007 | 0.6675 |
| No log | 4.89 | 450 | 1.3770 | 0.7857 | 0.6904 | 0.7095 | 0.6786 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0