---
license: apache-2.0
base_model: google/electra-small-discriminator
tags:
- generated_from_keras_callback
model-index:
- name: nguyennghia0902/electra-small-discriminator_0.0001_32_15e
  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_0.0001_32_15e

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: 0.5958
- Train End Logits Accuracy: 0.8298
- Train Start Logits Accuracy: 0.8077
- Validation Loss: 0.2565
- Validation End Logits Accuracy: 0.9243
- Validation Start Logits Accuracy: 0.9233
- Epoch: 14

## 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': 0.0001, 'decay_steps': 23445, '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 |
|:----------:|:-------------------------:|:---------------------------:|:---------------:|:------------------------------:|:--------------------------------:|:-----:|
| 3.0253     | 0.3302                    | 0.2968                      | 2.2414          | 0.4704                         | 0.4533                           | 0     |
| 2.3162     | 0.4597                    | 0.4260                      | 1.8267          | 0.5511                         | 0.5364                           | 1     |
| 2.0285     | 0.5160                    | 0.4813                      | 1.5472          | 0.6109                         | 0.5994                           | 2     |
| 1.8125     | 0.5587                    | 0.5287                      | 1.2995          | 0.6688                         | 0.6512                           | 3     |
| 1.6192     | 0.5963                    | 0.5677                      | 1.0973          | 0.7105                         | 0.7030                           | 4     |
| 1.4482     | 0.6341                    | 0.6066                      | 0.8998          | 0.7637                         | 0.7547                           | 5     |
| 1.2931     | 0.6694                    | 0.6423                      | 0.7622          | 0.7920                         | 0.7916                           | 6     |
| 1.1518     | 0.6980                    | 0.6741                      | 0.6412          | 0.8260                         | 0.8197                           | 7     |
| 1.0351     | 0.7240                    | 0.7025                      | 0.5316          | 0.8518                         | 0.8531                           | 8     |
| 0.9269     | 0.7488                    | 0.7270                      | 0.4671          | 0.8701                         | 0.8700                           | 9     |
| 0.8354     | 0.7714                    | 0.7489                      | 0.3836          | 0.8910                         | 0.8896                           | 10    |
| 0.7520     | 0.7904                    | 0.7699                      | 0.3342          | 0.9048                         | 0.9021                           | 11    |
| 0.6869     | 0.8056                    | 0.7848                      | 0.2983          | 0.9134                         | 0.9118                           | 12    |
| 0.6320     | 0.8209                    | 0.7994                      | 0.2667          | 0.9223                         | 0.9205                           | 13    |
| 0.5958     | 0.8298                    | 0.8077                      | 0.2565          | 0.9243                         | 0.9233                           | 14    |


### Framework versions

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