RathindraH/News-headline-classification

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

• Train Loss: 0.0289
• Train Accuracy: 0.9036
• Validation Loss: 0.3406
• Validation Accuracy: 0.9036
• Train F1 Macro: 0.8935
• Epoch: 4

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': 1250, '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 Accuracy	Validation Loss	Validation Accuracy	Train F1 Macro	Epoch
0.3963	0.8762	0.3037	0.8762	0.8633	0
0.1773	0.9	0.2750	0.9000	0.8893	1
0.0854	0.8976	0.3135	0.8976	0.8847	2
0.0483	0.9036	0.3294	0.9036	0.8947	3
0.0289	0.9036	0.3406	0.9036	0.8935	4

Framework versions

• Transformers 4.52.4
• TensorFlow 2.18.0
• Datasets 3.6.0
• Tokenizers 0.21.2