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bert-base-multilingual-cased-finetuned-PQuAD-3epochs – AI Model by Z-Jafari | AlphaNeural AI
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Z-Jafari
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bert-base-multilingual-cased-finetuned-PQuAD-3epochs
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transformers
tensorboard
safetensors
bert
question-answering
generated_from_trainer
fa
Z-Jafari/PQuAD
google-bert/bert-base-multilingual-cased
finetune
apache-2.0
endpoints_compatible
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bert-base-multilingual-cased-finetuned-PQuAD-3epochs
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: 0.8517
{'exact': 73.3816545863534, 'f1': 86.40922381247157, 'total': 8002, 'HasAns_exact': 67.41130091984232, 'HasAns_f1': 84.53459411093914, 'HasAns_total': 6088, 'NoAns_exact': 92.37199582027168, 'NoAns_f1': 92.37199582027168, 'NoAns_total': 1914, 'best_exact': 73.3816545863534, 'best_exact_thresh': 0.0, 'best_f1': 86.40922381247229, 'best_f1_thresh': 0.0}
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
0.7978
1.0
4051
0.8395
0.5898
2.0
8102
0.8184
0.4274
3.0
12153
0.8517
Framework versions
Transformers 4.57.3
Pytorch 2.9.0+cu126
Datasets 4.0.0
Tokenizers 0.22.1
