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: 0.2923
- Accuracy: 0.9409
- F1: 0.9043
- Precision: 0.9087
- Recall: 0.9
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 | 0.53 | 50 | 0.5324 | 0.8978 | 0.8032 | 0.9009 | 0.7572 |
| No log | 1.06 | 100 | 0.2795 | 0.9355 | 0.8967 | 0.8967 | 0.8967 |
| No log | 1.6 | 150 | 0.2561 | 0.9194 | 0.8772 | 0.8608 | 0.8972 |
| No log | 2.13 | 200 | 0.3274 | 0.9194 | 0.8635 | 0.8871 | 0.8444 |
| No log | 2.66 | 250 | 0.2756 | 0.9247 | 0.8819 | 0.8745 | 0.89 |
| No log | 3.19 | 300 | 0.4554 | 0.9032 | 0.8302 | 0.8696 | 0.8028 |
| No log | 3.72 | 350 | 0.2333 | 0.9462 | 0.9157 | 0.9075 | 0.9244 |
| No log | 4.26 | 400 | 0.4101 | 0.9247 | 0.8711 | 0.9013 | 0.8478 |
| No log | 4.79 | 450 | 0.2826 | 0.9409 | 0.9063 | 0.9021 | 0.9106 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0