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xlm-roberta-base-finetuned-IR_sum_QA – AI Model by Z-Jafari | AlphaNeural AI
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Z-Jafari
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xlm-roberta-base-finetuned-IR_sum_QA
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transformers
tensorboard
safetensors
xlm-roberta
question-answering
generated_from_trainer
fa
Z-Jafari/PersianQuAD
Z-Jafari/IR_sum_QA
FacebookAI/xlm-roberta-base
finetune
mit
endpoints_compatible
us
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xlm-roberta-base-finetuned-IR_sum_QA
This model is a fine-tuned version of
FacebookAI/xlm-roberta-base
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.8603
{'exact_match': 80.8, 'f1': 84.00235892762205}
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
0.9184
1.0
1762
0.8523
0.6327
2.0
3524
0.8606
0.4716
3.0
5286
0.8603
Framework versions
Transformers 4.57.3
Pytorch 2.9.0+cu126
Datasets 4.0.0
Tokenizers 0.22.1
