svenbl80/roberta-base-finetuned-new-mnli-run-6
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: 0.0245
- Validation Loss: 0.7259
- Train Accuracy: 0.8669
- 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', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 245430, '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-08, 'amsgrad': False}
- training_precision: float32
Training results
Train Loss | Validation Loss | Train Accuracy | Epoch |
---|---|---|---|
0.4536 | 0.3867 | 0.8534 | 0 |
0.3273 | 0.3665 | 0.8645 | 1 |
0.2440 | 0.4267 | 0.8591 | 2 |
0.1776 | 0.4708 | 0.8631 | 3 |
0.1281 | 0.5308 | 0.8597 | 4 |
0.0923 | 0.5570 | 0.8603 | 5 |
0.0666 | 0.6198 | 0.8631 | 6 |
0.0471 | 0.6758 | 0.8654 | 7 |
0.0336 | 0.7154 | 0.8652 | 8 |
0.0245 | 0.7259 | 0.8669 | 9 |
Framework versions
- Transformers 4.28.0
- TensorFlow 2.9.1
- Datasets 2.15.0
- Tokenizers 0.13.3
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