xlm-r-intent-espt

This model is a fine-tuned version of xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.9937
• Accuracy: 0.9962
• F1 Macro: 0.9960
• F1 Weighted: 0.9962
• F1 Cancelacion: 0.9912
• F1 Consulta General: 0.9983
• F1 Facturacion Pago: 0.9955
• F1 Feedback: 1.0
• F1 Gestion Cuenta: 0.9950
• F1 Modificacion Pedido: 0.9949
• F1 Queja: 0.9971
• F1 Reembolso: 0.9989
• F1 Seguimiento: 0.9932

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:

• learning_rate: 2e-05
• train_batch_size: 64
• eval_batch_size: 128
• seed: 42
• optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 0.1
• num_epochs: 3
• mixed_precision_training: Native AMP
• label_smoothing_factor: 0.1

Training results

Framework versions

• Transformers 5.0.0
• Pytorch 2.10.0+cu128
• Datasets 4.8.5
• Tokenizers 0.22.2