metadata
license: mit
base_model: Davlan/xlm-roberta-base-finetuned-arabic
tags:
- generated_from_keras_callback
model-index:
- name: betteib/xlm-tn-20epochs-lr
results: []
betteib/xlm-tn-20epochs-lr
This model is a fine-tuned version of Davlan/xlm-roberta-base-finetuned-arabic on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 7.2561
- Train Accuracy: 0.0273
- Validation Loss: 7.0588
- Validation Accuracy: 0.0289
- Epoch: 4
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': 'AdamWeightDecay', 'learning_rate': {'class_name': 'WarmUp', 'config': {'initial_learning_rate': 0.0001, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 0.0001, 'decay_steps': 4464, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'passive_serialization': True}, 'warmup_steps': 496, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.03}
- training_precision: float32
Training results
Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
---|---|---|---|---|
9.6176 | 0.0035 | 9.2319 | 0.0048 | 0 |
8.9356 | 0.0059 | 8.5303 | 0.0071 | 1 |
8.1494 | 0.0100 | 7.7161 | 0.0137 | 2 |
7.5554 | 0.0180 | 7.2709 | 0.0281 | 3 |
7.2561 | 0.0273 | 7.0588 | 0.0289 | 4 |
Framework versions
- Transformers 4.31.0
- TensorFlow 2.12.0
- Datasets 2.19.1
- Tokenizers 0.13.3