ModernBERT-base-finetuned-squad
This model is a fine-tuned version of answerdotai/ModernBERT-base on rajpurkar/squad dataset.
Model description
ModernBERT-base finetuned on rajpurkar/squad dataset for Extractive-QA. It performs better than the bert-base-uncased model on the same task & dataset.
Test results
Performance of the bert-base-uncased model on the same test data was:
{'exact_match': 81.18259224219489, 'f1': 88.67381321905516}
An improvement right !!
Training and evaluation data
rajpurkar/squad
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- 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: 3
- mixed_precision_training: Native AMP
Training results
Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 5.0.0
- Tokenizers 0.22.2