test_ot – AI Model by OnurT | AlphaNeural AI

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OnurT/
test_ot

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generated_from_keras_callback

google-bert/bert-base-cased

endpoints_compatible

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OnurT/test_ot

This model is a fine-tuned version of bert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:

Train Loss: 5.3310
Validation Loss: 5.5104
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': False, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 62, '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	Validation Loss	Epoch
5.8716	5.7167	0
5.5034	5.5328	1
5.3310	5.5104	2

Framework versions

Transformers 4.40.2
TensorFlow 2.16.1
Datasets 2.19.1
Tokenizers 0.19.1