|
|
--- |
|
|
license: mit |
|
|
base_model: indolem/indobert-base-uncased |
|
|
tags: |
|
|
- generated_from_keras_callback |
|
|
model-index: |
|
|
- name: Labira/LabiraEdu-v1.0x |
|
|
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. --> |
|
|
|
|
|
# Labira/LabiraEdu-v1.0x |
|
|
|
|
|
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: 0.1033 |
|
|
- Validation Loss: 4.1303 |
|
|
- Epoch: 33 |
|
|
|
|
|
## 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': 1100, '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 | Epoch | |
|
|
|:----------:|:---------------:|:-----:| |
|
|
| 5.0565 | 3.9761 | 0 | |
|
|
| 3.6621 | 3.2932 | 1 | |
|
|
| 3.0961 | 3.2587 | 2 | |
|
|
| 2.7357 | 3.2031 | 3 | |
|
|
| 2.3059 | 3.2519 | 4 | |
|
|
| 1.8933 | 3.4772 | 5 | |
|
|
| 1.9076 | 3.1664 | 6 | |
|
|
| 1.5492 | 3.4201 | 7 | |
|
|
| 1.2578 | 3.5190 | 8 | |
|
|
| 1.0478 | 3.4076 | 9 | |
|
|
| 1.0130 | 3.5961 | 10 | |
|
|
| 0.9073 | 3.4919 | 11 | |
|
|
| 0.7071 | 3.5013 | 12 | |
|
|
| 0.5616 | 4.0259 | 13 | |
|
|
| 0.4798 | 3.9766 | 14 | |
|
|
| 0.5938 | 3.8146 | 15 | |
|
|
| 0.6476 | 3.7065 | 16 | |
|
|
| 0.4264 | 4.1631 | 17 | |
|
|
| 0.5290 | 3.7455 | 18 | |
|
|
| 0.4637 | 3.6362 | 19 | |
|
|
| 0.3826 | 3.8389 | 20 | |
|
|
| 0.2876 | 3.7611 | 21 | |
|
|
| 0.2221 | 4.0540 | 22 | |
|
|
| 0.1752 | 4.0683 | 23 | |
|
|
| 0.1544 | 4.0452 | 24 | |
|
|
| 0.1600 | 4.0417 | 25 | |
|
|
| 0.1390 | 4.0668 | 26 | |
|
|
| 0.1134 | 4.0659 | 27 | |
|
|
| 0.0965 | 4.0700 | 28 | |
|
|
| 0.0820 | 4.2026 | 29 | |
|
|
| 0.0810 | 4.3008 | 30 | |
|
|
| 0.1166 | 4.0835 | 31 | |
|
|
| 0.0776 | 4.0886 | 32 | |
|
|
| 0.1033 | 4.1303 | 33 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.41.2 |
|
|
- TensorFlow 2.15.0 |
|
|
- Datasets 2.19.2 |
|
|
- Tokenizers 0.19.1 |
|
|
|
