Roberta-base-financial-sentiment-analysis

This model is a fine-tuned version of cardiffnlp/twitter-roberta-base-sentiment-latest on an unknown dataset. It achieves the following results on the evaluation set:

• Train Loss: 0.0013
• Train Accuracy: 1.0
• Validation Loss: 0.2910
• Validation Accuracy: 0.9431
• 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': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 5e-05, 'decay_steps': 3030, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
• training_precision: float32

Training results

Train Loss	Train Accuracy	Validation Loss	Validation Accuracy	Epoch
0.4682	0.8080	0.3497	0.8687	0
0.1674	0.9504	0.2655	0.9064	1
0.1139	0.9681	0.2639	0.9189	2
0.0847	0.9723	0.2259	0.9334	3
0.0454	0.9876	0.2156	0.9440	4
0.0262	0.9897	0.2593	0.9344	5
0.0136	0.9963	0.3786	0.9170	6
0.0043	0.9988	0.2589	0.9488	7
0.0042	0.9988	0.2866	0.9450	8
0.0013	1.0	0.2910	0.9431	9

Framework versions

• Transformers 4.32.0
• TensorFlow 2.12.0
• Datasets 2.14.4
• Tokenizers 0.13.3