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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_32
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_32
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: 2.5207
- Train End Logits Accuracy: 0.4119
- Train Start Logits Accuracy: 0.3790
- Validation Loss: 2.3751
- Validation End Logits Accuracy: 0.4375
- Validation Start Logits Accuracy: 0.4154
- Epoch: 9
- {'name': 'project02_google/electra-small-discriminator_1e-05_32',
'lnr': 1e-05,
'epoch': 10,
'batch_size': 32,
'time': 14461.474628210068,
'accuracy': 0.32024509190946604,
'f1_score': 0.4362419993977412}
## 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': 15630, '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 |
|:----------:|:-------------------------:|:---------------------------:|:---------------:|:------------------------------:|:--------------------------------:|:-----:|
| 4.0205 | 0.1761 | 0.1499 | 3.1750 | 0.2881 | 0.2533 | 0 |
| 3.1331 | 0.3100 | 0.2675 | 2.8517 | 0.3481 | 0.3184 | 1 |
| 2.9133 | 0.3429 | 0.3030 | 2.7096 | 0.3742 | 0.3479 | 2 |
| 2.7889 | 0.3674 | 0.3275 | 2.6031 | 0.3970 | 0.3685 | 3 |
| 2.7039 | 0.3811 | 0.3432 | 2.5304 | 0.4095 | 0.3853 | 4 |
| 2.6457 | 0.3903 | 0.3564 | 2.4704 | 0.4212 | 0.3956 | 5 |
| 2.5985 | 0.3968 | 0.3628 | 2.4328 | 0.4286 | 0.4026 | 6 |
| 2.5628 | 0.4050 | 0.3678 | 2.3987 | 0.4343 | 0.4117 | 7 |
| 2.5336 | 0.4085 | 0.3759 | 2.3774 | 0.4361 | 0.4142 | 8 |
| 2.5207 | 0.4119 | 0.3790 | 2.3751 | 0.4375 | 0.4154 | 9 |
### Framework versions
- Transformers 4.39.3
- TensorFlow 2.15.0
- Datasets 2.18.0
- Tokenizers 0.15.2
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