Finetune_XLM_R_large_QA

This model is a fine-tuned version of FacebookAI/xlm-roberta-large on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.4169
  • Exact: 72.8107
  • F1: 84.3095
  • Total: 3814
  • Hasans Exact: 72.8107
  • Hasans F1: 84.3095
  • Hasans Total: 3814
  • Best Exact: 72.8107
  • Best Exact Thresh: 0.0
  • Best F1: 84.3095
  • Best F1 Thresh: 0.0

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: 10
  • eval_batch_size: 10
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 20
  • 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: 10

Training results

Training Loss Epoch Step Validation Loss Exact F1 Total Hasans Exact Hasans F1 Hasans Total Best Exact Best Exact Thresh Best F1 Best F1 Thresh
1.1561 1.0 1364 1.1712 72.0241 82.5916 3814 72.0241 82.5916 3814 72.0241 0.0 82.5916 0.0
0.8571 2.0 2728 1.2553 75.0131 86.3057 3814 75.0131 86.3057 3814 75.0131 0.0 86.3057 0.0
0.6433 3.0 4092 1.3509 71.4473 82.3763 3814 71.4473 82.3763 3814 71.4473 0.0 82.3763 0.0
0.4305 4.0 5456 1.4169 72.8107 84.3095 3814 72.8107 84.3095 3814 72.8107 0.0 84.3095 0.0

Framework versions

  • Transformers 4.51.3
  • Pytorch 2.6.0+cu124
  • Datasets 3.6.0
  • Tokenizers 0.21.1
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