---
license: apache-2.0
base_model: google/electra-small-discriminator
tags:
- generated_from_keras_callback
model-index:
- name: nguyennghia0902/electra-small-discriminator_0.0005_16
  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. -->

# nguyennghia0902/electra-small-discriminator_0.0005_16

This model is a fine-tuned version of [google/electra-small-discriminator](https://huggingface.co/google/electra-small-discriminator) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 1.2099
- Train End Logits Accuracy: 0.6982
- Train Start Logits Accuracy: 0.6666
- Validation Loss: 0.7830
- Validation End Logits Accuracy: 0.7964
- Validation Start Logits Accuracy: 0.7852
- Epoch: 9

## 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': 0.0005, 'decay_steps': 31270, '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 | Train End Logits Accuracy | Train Start Logits Accuracy | Validation Loss | Validation End Logits Accuracy | Validation Start Logits Accuracy | Epoch |
|:----------:|:-------------------------:|:---------------------------:|:---------------:|:------------------------------:|:--------------------------------:|:-----:|
| 3.8593     | 0.1838                    | 0.1690                      | 2.9074          | 0.3506                         | 0.3319                           | 0     |
| 3.0501     | 0.3257                    | 0.2954                      | 2.5522          | 0.4171                         | 0.3859                           | 1     |
| 2.7183     | 0.3845                    | 0.3534                      | 2.2123          | 0.4803                         | 0.4547                           | 2     |
| 2.4780     | 0.4325                    | 0.4004                      | 1.9826          | 0.5248                         | 0.5046                           | 3     |
| 2.2672     | 0.4747                    | 0.4389                      | 1.8034          | 0.5660                         | 0.5425                           | 4     |
| 2.0640     | 0.5162                    | 0.4814                      | 1.5610          | 0.6207                         | 0.6037                           | 5     |
| 1.8439     | 0.5608                    | 0.5265                      | 1.3128          | 0.6811                         | 0.6639                           | 6     |
| 1.6214     | 0.6104                    | 0.5736                      | 1.0714          | 0.7326                         | 0.7206                           | 7     |
| 1.3990     | 0.6574                    | 0.6232                      | 0.8891          | 0.7744                         | 0.7630                           | 8     |
| 1.2099     | 0.6982                    | 0.6666                      | 0.7830          | 0.7964                         | 0.7852                           | 9     |


### Framework versions

- Transformers 4.39.3
- TensorFlow 2.15.0
- Datasets 2.18.0
- Tokenizers 0.15.2