sentiment-roberta-es-2025_II

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

  • Loss: 0.7531
  • F1 Macro: 0.6781
  • F1 Weighted: 0.6803
  • Accuracy: 0.6819

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: 1e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • 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_ratio: 0.1
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss F1 Macro F1 Weighted Accuracy
1.107 1.0 241 0.8921 0.5078 0.5163 0.5921
0.7969 2.0 482 0.7448 0.6745 0.6803 0.6816
0.6555 3.0 723 0.7315 0.7003 0.7042 0.7045
0.5117 4.0 964 0.8501 0.6990 0.7001 0.6982
0.3872 5.0 1205 0.9107 0.6765 0.6756 0.6701
0.3068 6.0 1446 0.9950 0.6910 0.6926 0.6920

Framework versions

  • Transformers 4.57.1
  • Pytorch 2.8.0+cu126
  • Datasets 4.0.0
  • Tokenizers 0.22.1
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