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xlm-roberta-large-finetuned-PersianQuAD-finetuned-pquad-1epochs – AI Model by Z-Jafari | AlphaNeural AI
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Z-Jafari
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xlm-roberta-large-finetuned-PersianQuAD-finetuned-pquad-1epochs
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transformers
tensorboard
safetensors
xlm-roberta
question-answering
generated_from_trainer
fa
Z-Jafari/pquad
mit
endpoints_compatible
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xlm-roberta-large-finetuned-PersianQuAD-finetuned-pquad-1epochs
This model is a fine-tuned version of
Z-Jafari/xlm-roberta-large-finetuned-PersianQuAD-3epochs
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.6292
{'exact': 77.43064233941514, 'f1': 89.71427942622053, 'total': 8002, 'HasAns_exact': 72.05978975032852, 'HasAns_f1': 88.20526674911574, 'HasAns_total': 6088, 'NoAns_exact': 94.5141065830721, 'NoAns_f1': 94.5141065830721, 'NoAns_total': 1914, 'best_exact': 77.43064233941514, 'best_exact_thresh': 0.0, 'best_f1': 89.71427942622121, '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: 1
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
0.5694
1.0
4020
0.6292
Framework versions
Transformers 4.57.3
Pytorch 2.9.0+cu126
Datasets 4.0.0
Tokenizers 0.22.1
