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---
license: apache-2.0
base_model: google/electra-small-discriminator
tags:
- generated_from_keras_callback
model-index:
- name: nguyennghia0902/electra-small-discriminator_1e-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_1e-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: 2.4725
- Train End Logits Accuracy: 0.4221
- Train Start Logits Accuracy: 0.3912
- Validation Loss: 2.2602
- Validation End Logits Accuracy: 0.4605
- Validation Start Logits Accuracy: 0.4399
- Epoch: 5
## 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': 1e-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 |
|:----------:|:-------------------------:|:---------------------------:|:---------------:|:------------------------------:|:--------------------------------:|:-----:|
| 3.6922 | 0.2260 | 0.1855 | 2.9570 | 0.3296 | 0.2955 | 0 |
| 2.9538 | 0.3373 | 0.2952 | 2.6908 | 0.3760 | 0.3455 | 1 |
| 2.7599 | 0.3690 | 0.3326 | 2.5323 | 0.4072 | 0.3820 | 2 |
| 2.6351 | 0.3920 | 0.3568 | 2.4256 | 0.4286 | 0.4008 | 3 |
| 2.5472 | 0.4089 | 0.3742 | 2.3283 | 0.4498 | 0.4264 | 4 |
| 2.4725 | 0.4221 | 0.3912 | 2.2602 | 0.4605 | 0.4399 | 5 |
### Framework versions
- Transformers 4.39.3
- TensorFlow 2.15.0
- Datasets 2.18.0
- Tokenizers 0.15.2
|