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vnktrmnb/xlm-roberta-base-FT-TyDiQA_AUQC-FT-TyDiQA_AUQC
This model is a fine-tuned version of vnktrmnb/xlm-roberta-base-FT-TyDiQA_AUQC on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.1588
- Train End Logits Accuracy: 0.9455
- Train Start Logits Accuracy: 0.9579
- Validation Loss: 0.6655
- Validation End Logits Accuracy: 0.8615
- Validation Start Logits Accuracy: 0.9035
- Epoch: 6
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': 2e-05, 'decay_steps': 9744, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
- training_precision: float32
Training results
| Train Loss | Train End Logits Accuracy | Train Start Logits Accuracy | Validation Loss | Validation End Logits Accuracy | Validation Start Logits Accuracy | Epoch |
|---|---|---|---|---|---|---|
| 0.7982 | 0.7889 | 0.8252 | 0.4654 | 0.8587 | 0.9119 | 0 |
| 0.6087 | 0.8296 | 0.8619 | 0.4771 | 0.8587 | 0.9063 | 1 |
| 0.4630 | 0.8631 | 0.8954 | 0.5086 | 0.8671 | 0.9119 | 2 |
| 0.3575 | 0.8913 | 0.9164 | 0.5528 | 0.8615 | 0.8993 | 3 |
| 0.2690 | 0.9131 | 0.9313 | 0.5861 | 0.8545 | 0.9035 | 4 |
| 0.2047 | 0.9312 | 0.9485 | 0.6629 | 0.8601 | 0.9021 | 5 |
| 0.1588 | 0.9455 | 0.9579 | 0.6655 | 0.8615 | 0.9035 | 6 |
Framework versions
- Transformers 4.32.0
- TensorFlow 2.12.0
- Datasets 2.14.4
- Tokenizers 0.13.3
