Arabert_Sentiment_Analysis

This model is a fine-tuned version of aubmindlab/bert-base-arabertv2 on an unknown dataset. It achieves the following results on the evaluation set:

• Train Loss: 0.6491
• Train Sparse Categorical Accuracy: 0.7488
• Validation Loss: 0.6851
• Validation Sparse Categorical Accuracy: 0.7252
• Epoch: 1

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': np.float32(5e-05), 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
• training_precision: float32

Training results

Train Loss	Train Sparse Categorical Accuracy	Validation Loss	Validation Sparse Categorical Accuracy	Epoch
0.8012	0.6563	0.6893	0.7187	0
0.6491	0.7488	0.6851	0.7252	1

Framework versions

• Transformers 4.52.4
• TensorFlow 2.19.0
• Datasets 3.6.0
• Tokenizers 0.21.1