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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_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
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