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robertuito-HUHU-task1

This model is a fine-tuned version of pysentimiento/robertuito-base-uncased for the HUHU Shared Task at IberLEF 2023. It was trained on a partition of the train set provided by the organizers.

Model description

This model is a fine-tuned version of pysentimiento/robertuito-base-uncased for the task of classifying a tweet (considered to be hurtful or conveying prejudice in some way) into humorous or non-humorous.

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': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': 3e-05, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
• training_precision: float32

Framework versions

• Transformers 4.30.2
• TensorFlow 2.12.0
• Tokenizers 0.13.3