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---
license: mit
base_model: indolem/indobert-base-uncased
tags:
- generated_from_keras_callback
model-index:
- name: damand2061/innermore-x-indobert-base-uncased
results: []
---
<!-- 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. -->
# damand2061/innermore-x-indobert-base-uncased
This model is a fine-tuned version of [indolem/indobert-base-uncased](https://huggingface.co/indolem/indobert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0053
- Validation Loss: 0.1740
- Validation Precision: 0.7319
- Validation Recall: 0.7644
- Validation F1: 0.7478
- Validation Accuracy: 0.9582
- Epoch: 14
## 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': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 0.0002, 'decay_steps': 420, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_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 | Validation Precision | Validation Recall | Validation F1 | Validation Accuracy | Epoch |
|:----------:|:---------------:|:--------------------:|:-----------------:|:-------------:|:-------------------:|:-----:|
| 0.7318 | 0.4161 | 0.1453 | 0.1156 | 0.1287 | 0.8751 | 0 |
| 0.3556 | 0.2296 | 0.5610 | 0.5111 | 0.5349 | 0.9324 | 1 |
| 0.2050 | 0.1668 | 0.6972 | 0.6756 | 0.6862 | 0.9521 | 2 |
| 0.1289 | 0.1603 | 0.6807 | 0.72 | 0.6998 | 0.9531 | 3 |
| 0.0875 | 0.1874 | 0.7281 | 0.7022 | 0.7149 | 0.9521 | 4 |
| 0.0754 | 0.1931 | 0.6653 | 0.7156 | 0.6895 | 0.9479 | 5 |
| 0.0416 | 0.1637 | 0.6935 | 0.7644 | 0.7273 | 0.9554 | 6 |
| 0.0238 | 0.1413 | 0.7598 | 0.7733 | 0.7665 | 0.9638 | 7 |
| 0.0152 | 0.1494 | 0.7479 | 0.8044 | 0.7752 | 0.9634 | 8 |
| 0.0152 | 0.1946 | 0.7061 | 0.7156 | 0.7108 | 0.9531 | 9 |
| 0.0128 | 0.1815 | 0.7241 | 0.7467 | 0.7352 | 0.9554 | 10 |
| 0.0072 | 0.1766 | 0.7210 | 0.7467 | 0.7336 | 0.9568 | 11 |
| 0.0080 | 0.1860 | 0.6987 | 0.7422 | 0.7198 | 0.9531 | 12 |
| 0.0089 | 0.1826 | 0.7227 | 0.7644 | 0.7430 | 0.9563 | 13 |
| 0.0053 | 0.1740 | 0.7319 | 0.7644 | 0.7478 | 0.9582 | 14 |
### Framework versions
- Transformers 4.38.2
- TensorFlow 2.15.0
- Tokenizers 0.15.2
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