metadata

license: mit
base_model: Davlan/xlm-roberta-base-finetuned-arabic
tags:
  - generated_from_keras_callback
model-index:
  - name: betteib/xlm-tn-20epochs
    results: []

betteib/xlm-tn-20epochs

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: 6.7068
Train Accuracy: 0.0290
Validation Loss: 6.6661
Validation Accuracy: 0.0290
Epoch: 14

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': 18848, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'passive_serialization': True}, 'warmup_steps': 992, '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
9.7281	0.0031	9.4281	0.0045	0
9.2184	0.0051	8.9814	0.0060	1
8.7336	0.0068	8.4005	0.0084	2
8.1287	0.0109	7.7969	0.0133	3
7.6665	0.0159	7.4295	0.0222	4
7.3938	0.0233	7.1783	0.0289	5
7.2079	0.0287	7.0257	0.0286	6
7.0785	0.0292	6.9028	0.0291	7
6.9777	0.0294	6.8739	0.0287	8
6.9034	0.0292	6.8083	0.0281	9
6.8549	0.0292	6.8099	0.0280	10
6.7978	0.0292	6.7450	0.0286	11
6.7555	0.0291	6.7420	0.0281	12
6.7267	0.0293	6.6804	0.0291	13
6.7068	0.0290	6.6661	0.0290	14

Framework versions

Transformers 4.31.0
TensorFlow 2.12.0
Datasets 2.19.1
Tokenizers 0.13.3