Roberta_monant

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

• Loss: 0.4024
• Accuracy: 0.836
• Auc: 0.739
• Precision: 0.0
• Recall: 0.0
• F1: 0.0
• F1-macro: 0.455
• F1-micro: 0.836
• F1-weighted: 0.761

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: 8
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 16
• 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
• num_epochs: 2
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Auc	Precision	Recall	F1	F1-macro	F1-micro	F1-weighted
0.5476	0.8475	50	0.4161	0.836	0.693	0.0	0.0	0.0	0.455	0.836	0.761
0.4961	1.6949	100	0.4024	0.836	0.739	0.0	0.0	0.0	0.455	0.836	0.761

Framework versions

• Transformers 4.55.2
• Pytorch 2.8.0+cu126
• Datasets 4.0.0
• Tokenizers 0.21.4