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cruiser/roberta_tensorflow_test
This model is a fine-tuned version of cardiffnlp/twitter-xlm-roberta-base-sentiment on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.1366
- Train Accuracy: 0.9537
- Validation Loss: 0.8098
- Validation Accuracy: 0.7875
- Epoch: 5
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', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 5e-05, 'decay_steps': 34350, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, '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 |
|---|---|---|---|---|
| 0.6043 | 0.7502 | 0.5449 | 0.7756 | 0 |
| 0.4868 | 0.8044 | 0.5104 | 0.7807 | 1 |
| 0.3846 | 0.8472 | 0.5949 | 0.7705 | 2 |
| 0.2873 | 0.8908 | 0.6515 | 0.7858 | 3 |
| 0.1965 | 0.9293 | 0.7051 | 0.7813 | 4 |
| 0.1366 | 0.9537 | 0.8098 | 0.7875 | 5 |
Framework versions
- Transformers 4.20.1
- TensorFlow 2.9.2
- Datasets 2.1.0
- Tokenizers 0.12.1
