xlm-roberta-base-Urdu1M-finetuned

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xlm-roberta-base-Urdu1M-finetuned

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: 1.4698
• Validation Loss: 1.2016
• Model Perplexity on Validation set: 3.31
• Number of Epochs: 7

Training hyperparameters

The following hyperparameters were used during training:

• optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'module': 'transformers.optimization_tf', 'class_name': 'WarmUp', 'config': {'initial_learning_rate': 2e-05, 'decay_schedule_fn': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 80460, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'warmup_steps': 1000, 'power': 1.0, 'name': None}, 'registered_name': 'WarmUp'}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
• training_precision: mixed_float16

Training results

Framework versions

• Transformers 4.31.0
• TensorFlow 2.13.0
• Datasets 2.14.4
• Tokenizers 0.13.3

Please refer to the paper "Fake News Classification in Urdu: A Domain Adaptation Approach for a Low-Resource Language" for more details.