---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: Electro98/my_awesome_model_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. -->

# Electro98/my_awesome_model_v2

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: 0.1620
- Validation Loss: 0.1617
- Train F1: 0.0731
- Train Accuracy: 0.1217
- Epoch: 12

## 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': 1056100, '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 |
|:----------:|:---------------:|:--------:|:--------------:|:-----:|
| 0.1841     | 0.1586          | 0.0441   | 0.0484         | 0     |
| 0.1733     | 0.1553          | 0.0447   | 0.0537         | 1     |
| 0.1628     | 0.1516          | 0.0757   | 0.0990         | 2     |
| 0.1600     | 0.1559          | 0.0700   | 0.1263         | 3     |
| 0.1634     | 0.1549          | 0.0662   | 0.0956         | 4     |
| 0.1620     | 0.1526          | 0.0611   | 0.0777         | 5     |
| 0.1622     | 0.1718          | 0.0809   | 0.0865         | 6     |
| 0.1625     | 0.1577          | 0.0498   | 0.0942         | 7     |
| 0.1649     | 0.1566          | 0.0799   | 0.1404         | 8     |
| 0.1684     | 0.1585          | 0.0700   | 0.1262         | 9     |
| 0.1628     | 0.1582          | 0.0802   | 0.1112         | 10    |
| 0.1605     | 0.1614          | 0.0651   | 0.1065         | 11    |
| 0.1620     | 0.1617          | 0.0731   | 0.1217         | 12    |


### Framework versions

- Transformers 4.27.4
- TensorFlow 2.10.0
- Datasets 2.18.0
- Tokenizers 0.13.3