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bert-base-multilingual-cased-finetuned-Gemma3_Scored-scr-0.65-sim-0.9 – AI Model by Z-Jafari | AlphaNeural AI
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Z-Jafari
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bert-base-multilingual-cased-finetuned-Gemma3_Scored-scr-0.65-sim-0.9
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transformers
tensorboard
safetensors
bert
question-answering
generated_from_trainer
Z-Jafari/PersianQuAD
Z-Jafari/Gemma3_Scored
google-bert/bert-base-multilingual-cased
finetune
apache-2.0
endpoints_compatible
us
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bert-base-multilingual-cased-finetuned-Gemma3_Scored-scr-0.65-sim-0.9
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: 0.9818
{'exact_match': 77.8, 'f1': 81.72182644153229}
augmented dataset: 6365 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
0.8655
1.0
1967
0.9049
0.5518
2.0
3934
0.8900
0.352
3.0
5901
0.9818
Framework versions
Transformers 4.57.3
Pytorch 2.9.0+cu126
Datasets 4.0.0
Tokenizers 0.22.1
