v_model – AI Model by NourMohamed91 | AlphaNeural AI

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NourMohamed91/
v_model

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gp-tar4/QA_FineTuned_Arabert

endpoints_compatible

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NourMohamed91/v_model

This model is a fine-tuned version of gp-tar4/QA_FineTuned_Arabert on an unknown dataset. It achieves the following results on the evaluation set:

Train Loss: 0.0040
Validation Loss: 0.0302
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': 2e-05, 'decay_steps': 210, '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
2.0085	0.3095	0
0.1496	0.0399	1
0.0319	0.0350	2
0.0195	0.0327	3
0.0125	0.0162	4
0.0067	0.0239	5
0.0038	0.0242	6
0.0045	0.0239	7
0.0173	0.0323	8
0.0040	0.0302	9

Framework versions

Transformers 4.42.4
TensorFlow 2.15.0
Datasets 2.20.0
Tokenizers 0.19.1