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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_5e-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_5e-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: 1.2106
- Train End Logits Accuracy: 0.6868
- Train Start Logits Accuracy: 0.6616
- Validation Loss: 0.8171
- Validation End Logits Accuracy: 0.7790
- Validation Start Logits Accuracy: 0.7721
- 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': 5e-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 |
|:----------:|:-------------------------:|:---------------------------:|:---------------:|:------------------------------:|:--------------------------------:|:-----:|
| 3.0718 | 0.3197 | 0.2882 | 2.3841 | 0.4358 | 0.4158 | 0 |
| 2.4050 | 0.4412 | 0.4100 | 1.9607 | 0.5286 | 0.5126 | 1 |
| 2.1054 | 0.5011 | 0.4714 | 1.6636 | 0.5884 | 0.5755 | 2 |
| 1.9002 | 0.5421 | 0.5122 | 1.4655 | 0.6276 | 0.6173 | 3 |
| 1.7347 | 0.5741 | 0.5496 | 1.2668 | 0.6755 | 0.6654 | 4 |
| 1.5852 | 0.6070 | 0.5807 | 1.1348 | 0.7053 | 0.6950 | 5 |
| 1.4627 | 0.6330 | 0.6039 | 1.0051 | 0.7336 | 0.7269 | 6 |
| 1.3557 | 0.6545 | 0.6285 | 0.9167 | 0.7577 | 0.7491 | 7 |
| 1.2715 | 0.6741 | 0.6457 | 0.8508 | 0.7708 | 0.7643 | 8 |
| 1.2106 | 0.6868 | 0.6616 | 0.8171 | 0.7790 | 0.7721 | 9 |
### Framework versions
- Transformers 4.39.3
- TensorFlow 2.15.0
- Datasets 2.18.0
- Tokenizers 0.15.2
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