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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_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
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