svenbl80/roberta-base-finetuned-new-mnli-run-5
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: 0.0252
- Validation Loss: 0.6904
- Train Accuracy: 0.8664
- 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 |
---|---|---|---|
0.4561 | 0.3859 | 0.8565 | 0 |
0.3292 | 0.3796 | 0.8647 | 1 |
0.2467 | 0.3988 | 0.8592 | 2 |
0.1801 | 0.4358 | 0.8620 | 3 |
0.1309 | 0.4774 | 0.8631 | 4 |
0.0945 | 0.5281 | 0.8590 | 5 |
0.0682 | 0.5577 | 0.8659 | 6 |
0.0486 | 0.6420 | 0.8636 | 7 |
0.0348 | 0.6607 | 0.8688 | 8 |
0.0252 | 0.6904 | 0.8664 | 9 |
Framework versions
- Transformers 4.28.0
- TensorFlow 2.9.1
- Datasets 2.15.0
- Tokenizers 0.13.3
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