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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
