metadata

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: []

nguyennghia0902/electra-small-discriminator_1e-05_16

This model is a fine-tuned version of google/electra-small-discriminator on an unknown dataset. It achieves the following results on the evaluation set:

Train Loss: 2.7599
Train End Logits Accuracy: 0.3690
Train Start Logits Accuracy: 0.3326
Validation Loss: 2.5323
Validation End Logits Accuracy: 0.4072
Validation Start Logits Accuracy: 0.3820
Epoch: 2

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

Framework versions

Transformers 4.39.3
TensorFlow 2.15.0
Datasets 2.18.0
Tokenizers 0.15.2