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: 1.2438
{'exact_match': 77.0, 'f1': 80.647722353326}
augmented dataset: 2744 rows

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

Training results

Training Loss	Epoch	Step	Validation Loss
1.0072	1.0	1463	1.0771
0.5639	2.0	2926	1.0888
0.3282	3.0	4389	1.2438

Framework versions

Transformers 4.57.3
Pytorch 2.9.0+cu126
Datasets 4.0.0
Tokenizers 0.22.1

Z-Jafari/bert-fa-base-uncased-finetuned-IR_sum_Scored-scr-0.65-sim-1

bert-fa-base-uncased-finetuned-IR_sum_Scored-scr-0.65-sim-1

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Z-Jafari/
bert-fa-base-uncased-finetuned-IR_sum_Scored-scr-0.65-sim-1