robbery_dataset_tf_finetuned_20230213_delitos_validados

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robbery_dataset_tf_finetuned_20230213_delitos_validados

This model is a fine-tuned version of distilbert-base-multilingual-cased on an unknown dataset. It achieves the following results on the evaluation set:

• Train Loss: 0.1837
• Train Sparse Categorical Accuracy: 0.9465
• Validation Loss: 0.3629
• Validation Sparse Categorical Accuracy: 0.8995
• Epoch: 9

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': '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-06, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
• training_precision: float32

Training results

Framework versions

• Transformers 4.26.1
• TensorFlow 2.11.0
• Datasets 2.9.0
• Tokenizers 0.13.2