---
library_name: transformers
license: mit
base_model: FacebookAI/xlm-roberta-large
tags:
- generated_from_trainer
model-index:
- name: xlm-roberta-large-finetuned-pquad-1epochs
  results: []
datasets:
- Z-Jafari/PQuAD
language:
- fa
metrics:
- f1
- exact_match
pipeline_tag: question-answering
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# xlm-roberta-large-finetuned-pquad-1epochs

This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6493
- {'exact': 76.86828292926768,
 'f1': 89.39013257952286,
 'total': 8002,
 'HasAns_exact': 71.63272010512483,
 'HasAns_f1': 88.09130106789452,
 'HasAns_total': 6088,
 'NoAns_exact': 93.521421107628,
 'NoAns_f1': 93.521421107628,
 'NoAns_total': 1914,
 'best_exact': 76.86828292926768,
 'best_exact_thresh': 0.0,
 'best_f1': 89.3901325795236,
 '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 |
|:-------------:|:-----:|:----:|:---------------:|
| 0.5923        | 1.0   | 4020 | 0.6493          |


### Framework versions

- Transformers 4.57.3
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1