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XLMRobertaz
This model is a fine-tuned version of xlm-roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.5404
- Train End Logits Accuracy: 0.8404
- Train Start Logits Accuracy: 0.7997
- Validation Loss: 1.0036
- Validation End Logits Accuracy: 0.7448
- Validation Start Logits Accuracy: 0.7148
- Epoch: 3
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': 22396, '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 | Train End Logits Accuracy | Train Start Logits Accuracy | Validation Loss | Validation End Logits Accuracy | Validation Start Logits Accuracy | Epoch |
|---|---|---|---|---|---|---|
| 1.2940 | 0.6600 | 0.6215 | 0.9820 | 0.7357 | 0.7047 | 0 |
| 0.8412 | 0.7666 | 0.7252 | 0.9281 | 0.7473 | 0.7137 | 1 |
| 0.6629 | 0.8091 | 0.7681 | 0.9387 | 0.7450 | 0.7130 | 2 |
| 0.5404 | 0.8404 | 0.7997 | 1.0036 | 0.7448 | 0.7148 | 3 |
Framework versions
- Transformers 4.20.1
- TensorFlow 2.6.4
- Datasets 2.1.0
- Tokenizers 0.12.1
