---
license: apache-2.0
base_model: google/electra-small-discriminator
tags:
- generated_from_keras_callback
model-index:
- name: nguyennghia0902/electra-small-discriminator_0.0001_16_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_16_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: 1.0610
- Train End Logits Accuracy: 0.7222
- Train Start Logits Accuracy: 0.6963
- Validation Loss: 0.5471
- Validation End Logits Accuracy: 0.8490
- Validation Start Logits Accuracy: 0.8476
- Epoch: 7

## 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': 46905, '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 |
|:----------:|:-------------------------:|:---------------------------:|:---------------:|:------------------------------:|:--------------------------------:|:-----:|
| 2.9418     | 0.3441                    | 0.3115                      | 2.1831          | 0.4777                         | 0.4649                           | 0     |
| 2.2767     | 0.4696                    | 0.4357                      | 1.7802          | 0.5643                         | 0.5481                           | 1     |
| 1.9907     | 0.5234                    | 0.4941                      | 1.5055          | 0.6229                         | 0.6068                           | 2     |
| 1.7630     | 0.5690                    | 0.5440                      | 1.2348          | 0.6824                         | 0.6708                           | 3     |
| 1.5637     | 0.6086                    | 0.5842                      | 1.0345          | 0.7291                         | 0.7190                           | 4     |
| 1.3785     | 0.6500                    | 0.6241                      | 0.8309          | 0.7823                         | 0.7724                           | 5     |
| 1.2118     | 0.6880                    | 0.6604                      | 0.6918          | 0.8105                         | 0.8116                           | 6     |
| 1.0610     | 0.7222                    | 0.6963                      | 0.5471          | 0.8490                         | 0.8476                           | 7     |


### Framework versions

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