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indobert-base-uncased-lora-nergrit
apwic/indobert-base-uncased-lora-nergrit
indobert-base-uncased-lora-nergrit is a machine learning model from apwic. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as mit.
probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- peft
- License
- mit
- Model type
- bert
- Access
- Public
- Created
- Oct 23, 2023
- Updated
- Oct 24, 2023
- SHA
- 33fcfe8a
Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
apwic/indobert-base-uncased-lora-nergrit
This model is a fine-tuned version of indolem/indobert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.1277
- Validation Loss: 0.1806
- Train Accuracy: 0.9468
- Epoch: 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:
- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 2352, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32
Training results
| Train Loss | Validation Loss | Train Accuracy | Epoch |
|---|---|---|---|
| 0.4709 | 0.2069 | 0.9399 | 0 |
| 0.1823 | 0.1855 | 0.9441 | 1 |
| 0.1402 | 0.1806 | 0.9468 | 2 |
| 0.1287 | 0.1806 | 0.9468 | 3 |
| 0.1280 | 0.1806 | 0.9468 | 4 |
| 0.1278 | 0.1806 | 0.9468 | 5 |
| 0.1285 | 0.1806 | 0.9468 | 6 |
| 0.1279 | 0.1806 | 0.9468 | 7 |
| 0.1289 | 0.1806 | 0.9468 | 8 |
| 0.1277 | 0.1806 | 0.9468 | 9 |
Framework versions
- PEFT 0.5.0
- PEFT 0.5.0
- Transformers 4.33.0
- TensorFlow 2.12.0
- Datasets 2.14.6
- Tokenizers 0.13.3
- Library
- peft
- Type
- bert
- License
- mit
- Created
- Oct 23, 2023
- Updated
- Oct 24, 2023