xlm-tn-20epochs / README.md
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Training in progress epoch 14
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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