electra-small-discriminator_1e-05_16

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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: 2.2953
• Train End Logits Accuracy: 0.4633
• Train Start Logits Accuracy: 0.4286
• Validation Loss: 2.1111
• Validation End Logits Accuracy: 0.4964
• Validation Start Logits Accuracy: 0.4762
• Epoch: 9
• {'name': 'project02_google/electra-small-discriminator_1e-05_16', 'lnr': 1e-05, 'epoch': 10, 'batch_size': 16, 'time': 15051.128346920013, 'accuracy': 0, 'f1_score': 0}

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

Framework versions

• Transformers 4.39.3
• TensorFlow 2.15.0
• Datasets 2.18.0
• Tokenizers 0.15.2