---
license: apache-2.0
base_model: google/electra-small-discriminator
tags:
- generated_from_keras_callback
model-index:
- name: nguyennghia0902/electra-small-discriminator_2e-05_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_2e-05_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: 1.8204
- Train End Logits Accuracy: 0.5584
- Train Start Logits Accuracy: 0.5303
- Validation Loss: 1.5543
- Validation End Logits Accuracy: 0.6127
- Validation Start Logits Accuracy: 0.5972
- 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': 2e-05, '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 |
|:----------:|:-------------------------:|:---------------------------:|:---------------:|:------------------------------:|:--------------------------------:|:-----:|
| 3.3122     | 0.2821                    | 0.2485                      | 2.6648          | 0.3797                         | 0.3553                           | 0     |
| 2.6687     | 0.3873                    | 0.3537                      | 2.3167          | 0.4510                         | 0.4297                           | 1     |
| 2.4256     | 0.4356                    | 0.4051                      | 2.1007          | 0.4965                         | 0.4787                           | 2     |
| 2.2600     | 0.4678                    | 0.4373                      | 1.9512          | 0.5271                         | 0.5112                           | 3     |
| 2.1384     | 0.4927                    | 0.4626                      | 1.8342          | 0.5512                         | 0.5353                           | 4     |
| 2.0404     | 0.5101                    | 0.4814                      | 1.7279          | 0.5752                         | 0.5598                           | 5     |
| 1.9575     | 0.5275                    | 0.4978                      | 1.6628          | 0.5890                         | 0.5718                           | 6     |
| 1.8962     | 0.5405                    | 0.5127                      | 1.5958          | 0.6047                         | 0.5877                           | 7     |
| 1.8478     | 0.5503                    | 0.5211                      | 1.5622          | 0.6112                         | 0.5964                           | 8     |
| 1.8204     | 0.5584                    | 0.5303                      | 1.5543          | 0.6127                         | 0.5972                           | 9     |


### Framework versions

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