metadata

license: mit
base_model: Davlan/xlm-roberta-base-finetuned-arabic
tags:
  - generated_from_keras_callback
model-index:
  - name: betteib/xlm-mlm-tn
    results: []

betteib/xlm-mlm-tn

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: 8.1277
Train Accuracy: 0.0048
Validation Loss: 8.1367
Validation Accuracy: 0.0046
Epoch: 1

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': 118, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'passive_serialization': True}, 'warmup_steps': 6, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.001}
training_precision: float32

Training results

Train Loss	Train Accuracy	Validation Loss	Validation Accuracy	Epoch
8.7004	0.0046	8.1656	0.0046	0
8.1277	0.0048	8.1367	0.0046	1

Framework versions

Transformers 4.31.0
TensorFlow 2.12.0
Datasets 2.19.1
Tokenizers 0.13.3