bert-base-multilingual-cased-finetuned-PersianQuAD_Factoid_Test

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

• Loss: 0.7142
• {'exact_match': 79.5673076923077, 'f1': 82.23521270396266}

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
0.8703	1.0	1168	0.7337
0.5434	2.0	2336	0.6869
0.3244	3.0	3504	0.7142

Framework versions

• Transformers 5.0.0
• Pytorch 2.10.0+cu128
• Datasets 4.0.0
• Tokenizers 0.22.2