---
license: mit
tags:
- generated_from_trainer
model-index:
- name: xlm-roberta-base-finetuned-pquad-squad
  results: []
datasets:
- Gholamreza/pquad
- squad_v2
language:
- en
- fa
metrics:
- f1
- exact_match
library_name: transformers
---

<!-- 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-base-finetuned-pquad-squad

This model is a version of [xlm-roberta-base](https://huggingface.co./xlm-roberta-base) fine-tuned jointly on PQuAD and SQuAD_v2 datasets.

## Results
Trained only for 3000/12000 steps (1/4th of an epoch) due to computational restrictions.

{'exact': 66.57766134314072,
 'f1': 73.79323871739385,
 'total': 19849,
 'HasAns_exact': 64.51396460622327,
 'HasAns_f1': 76.52620945245035,
 'HasAns_total': 11923,
 'NoAns_exact': 69.68205904617714,
 'NoAns_f1': 69.68205904617714,
 'NoAns_total': 7926,
 'best_exact': 66.57766134314072,
 'best_exact_thresh': 0.0,
 'best_f1': 73.79323871739267,
 'best_f1_thresh': 0.0}

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1

### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2