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---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: Electro98/my_awesome_model
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. -->
# Electro98/my_awesome_model
This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.1447
- Validation Loss: 0.1826
- Train F1: 0.1535
- Train Accuracy: 0.2915
- Epoch: 19
## 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', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 135650, '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}
- training_precision: float32
### Training results
| Train Loss | Validation Loss | Train F1 | Train Accuracy | Epoch |
|:----------:|:---------------:|:--------:|:--------------:|:-----:|
| 0.2025 | 0.1689 | 0.0051 | 0.0039 | 0 |
| 0.1938 | 0.1780 | 0.0683 | 0.1028 | 1 |
| 0.2008 | 0.1897 | 0.0055 | 0.0112 | 2 |
| 0.1826 | 0.1879 | 0.0754 | 0.0988 | 3 |
| 0.1740 | 0.1792 | 0.0848 | 0.0989 | 4 |
| 0.1909 | 0.1799 | 0.0294 | 0.1297 | 5 |
| 0.1983 | 0.1786 | 0.0675 | 0.2112 | 6 |
| 0.1905 | 0.1820 | 0.0962 | 0.2360 | 7 |
| 0.2033 | 0.1628 | 0.0778 | 0.2005 | 8 |
| 0.1653 | 0.1602 | 0.1280 | 0.2644 | 9 |
| 0.1656 | 0.1609 | 0.0836 | 0.2042 | 10 |
| 0.1584 | 0.1572 | 0.1323 | 0.2292 | 11 |
| 0.1633 | 0.1770 | 0.1140 | 0.2231 | 12 |
| 0.1588 | 0.1595 | 0.1145 | 0.2097 | 13 |
| 0.1538 | 0.1798 | 0.1448 | 0.3142 | 14 |
| 0.1552 | 0.1656 | 0.1531 | 0.2974 | 15 |
| 0.1514 | 0.1692 | 0.1905 | 0.3193 | 16 |
| 0.1490 | 0.1675 | 0.1692 | 0.2950 | 17 |
| 0.1462 | 0.1736 | 0.1522 | 0.2900 | 18 |
| 0.1447 | 0.1826 | 0.1535 | 0.2915 | 19 |
### Framework versions
- Transformers 4.27.4
- TensorFlow 2.10.0
- Datasets 2.18.0
- Tokenizers 0.13.3
|