KIPBERT
This model is a fine-tuned version of indolem/indobert-base-uncased on the id_nergrit_corpus dataset. It achieves the following results on the evaluation set:
- Loss: 0.1731
- Precision: 0.8058
- Recall: 0.8325
- F1: 0.8189
- Accuracy: 0.9503
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: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.4926 | 1.0 | 784 | 0.1810 | 0.7860 | 0.8172 | 0.8013 | 0.9450 |
| 0.1627 | 2.0 | 1568 | 0.1731 | 0.8058 | 0.8325 | 0.8189 | 0.9503 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
- Downloads last month
- 28
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Model tree for kiipliwooke/KIPBERT
Base model
indolem/indobert-base-uncasedDataset used to train kiipliwooke/KIPBERT
Evaluation results
- Precision on id_nergrit_corpustest set self-reported0.806
- Recall on id_nergrit_corpustest set self-reported0.833
- F1 on id_nergrit_corpustest set self-reported0.819
- Accuracy on id_nergrit_corpustest set self-reported0.950