xlm-roberta-mushroom-qa
This model was fine-tuned to tackle SemEval 2025 Task3: Mu-SHROOM. Its task is to extract hallucination spans from large language model output.
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Fine-tuning hyperparameters
The following hyperparameters were used during fine-tuning:
- learning_rate: 5e-02
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 4.0
Framework versions
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.0
- Tokenizers 0.21.0
