Abhra-loony/financial_text_sentiment_classification_model
This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.4016
- Validation Loss: 0.4311
- Train Accuracy: 0.7930
- 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-06, 'decay_steps': 1460, '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 | Train Accuracy | Epoch |
---|---|---|---|
0.9596 | 0.8704 | 0.5449 | 0 |
0.7972 | 0.7030 | 0.6689 | 1 |
0.5561 | 0.4668 | 0.7921 | 2 |
0.4376 | 0.4376 | 0.7904 | 3 |
0.4016 | 0.4311 | 0.7930 | 4 |
Framework versions
- Transformers 4.42.4
- TensorFlow 2.17.0
- Datasets 2.21.0
- Tokenizers 0.19.1
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Model tree for Abhra-loony/financial_text_sentiment_classification_model
Base model
FacebookAI/roberta-base