checkworthy-binary-classification-training-debert-1755503743

This model is a fine-tuned version of microsoft/deberta-v3-large on the Text Check-Worthiness (English).

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: 2.1106713456200193e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 16
• optimizer: Use OptimizerNames.PAGED_ADAMW with betas=(0.9348819720458172,0.9285998615546803) and epsilon=1.9972958061508847e-07 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: polynomial
• lr_scheduler_warmup_ratio: 0.12890328790683203
• lr_scheduler_warmup_steps: 488
• num_epochs: 10

Training results

Framework versions

• Transformers 4.55.2
• Pytorch 2.6.0+cu124
• Datasets 4.0.0
• Tokenizers 0.21.4