bert-fa-base-uncased-finetuned-IR_sum_QA

This model is a fine-tuned version of HooshvareLab/bert-fa-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 1.2566
• {'exact_match': 78.1, 'f1': 81.18920440326781}

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: 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
• num_epochs: 3
• mixed_precision_training: Native AMP
• fp16 = True

Training results

Training Loss	Epoch	Step	Validation Loss
0.8955	1.0	1590	1.0928
0.5267	2.0	3180	1.0997
0.3214	3.0	4770	1.2566

Framework versions

• Transformers 4.57.3
• Pytorch 2.9.0+cu126
• Datasets 4.0.0
• Tokenizers 0.22.1