metadata
license: mit
base_model: indobenchmark/indobert-base-p2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: eksplorasi_model
results: []
eksplorasi_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: 0.3647
- Accuracy: 0.8529
- F1: 0.9153
- Precision: 0.8710
- Recall: 0.9643
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 | 17 | 0.3647 | 0.8529 | 0.9153 | 0.8710 | 0.9643 |
| No log | 2.0 | 34 | 0.4506 | 0.8529 | 0.9091 | 0.9259 | 0.8929 |
| No log | 3.0 | 51 | 0.5964 | 0.8529 | 0.9153 | 0.8710 | 0.9643 |
| No log | 4.0 | 68 | 0.6727 | 0.8235 | 0.8929 | 0.8929 | 0.8929 |
| No log | 5.0 | 85 | 0.6488 | 0.8235 | 0.8966 | 0.8667 | 0.9286 |
| No log | 6.0 | 102 | 0.6798 | 0.8529 | 0.9123 | 0.8966 | 0.9286 |
| No log | 7.0 | 119 | 0.7034 | 0.8529 | 0.9123 | 0.8966 | 0.9286 |
| No log | 8.0 | 136 | 0.6960 | 0.8529 | 0.9123 | 0.8966 | 0.9286 |
| No log | 9.0 | 153 | 0.7040 | 0.8529 | 0.9123 | 0.8966 | 0.9286 |
| No log | 10.0 | 170 | 0.7053 | 0.8529 | 0.9123 | 0.8966 | 0.9286 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0