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---
tags:
- generated_from_keras_callback
model-index:
- name: aadhistii/tsel-finetune-indobert-base-p1-2k-formal-v2
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. -->
# aadhistii/tsel-finetune-indobert-base-p1-2k-formal-v2
This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0105
- Validation Loss: 1.0450
- Train Precision: 0.7633
- Train Recall: 0.7633
- Train F1: 0.7633
- Epoch: 8
## 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': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 940, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
- training_precision: float32
### Training results
| Train Loss | Validation Loss | Train Precision | Train Recall | Train F1 | Epoch |
|:----------:|:---------------:|:---------------:|:------------:|:--------:|:-----:|
| 0.7881 | 0.5850 | 0.7660 | 0.7660 | 0.7660 | 0 |
| 0.4468 | 0.6147 | 0.7447 | 0.7447 | 0.7447 | 1 |
| 0.2292 | 0.7075 | 0.7633 | 0.7633 | 0.7633 | 2 |
| 0.1116 | 0.8423 | 0.7473 | 0.7473 | 0.7473 | 3 |
| 0.0603 | 0.8702 | 0.7793 | 0.7793 | 0.7793 | 4 |
| 0.0273 | 0.9224 | 0.7606 | 0.7606 | 0.7606 | 5 |
| 0.0152 | 1.0343 | 0.7394 | 0.7394 | 0.7394 | 6 |
| 0.0149 | 1.0186 | 0.7473 | 0.7473 | 0.7473 | 7 |
| 0.0105 | 1.0450 | 0.7633 | 0.7633 | 0.7633 | 8 |
### Framework versions
- Transformers 4.42.3
- TensorFlow 2.15.0
- Datasets 2.20.0
- Tokenizers 0.19.1
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