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# 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
{"language": ["en", "fa"], "license": "mit", "library_name": "transformers", "tags": ["generated_from_trainer"], "datasets": ["Gholamreza/pquad", "squad_v2"], "metrics": ["f1", "exact_match"], "model-index": [{"name": "xlm-roberta-base-finetuned-pquad-squad", "results": []}]}
transformers pytorch tensorboard xlm-roberta question-answering generated_from_trainer en fa dataset:Gholamreza/pquad dataset:squad_v2 license:mit endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #xlm-roberta #question-answering #generated_from_trainer #en #fa #dataset-Gholamreza/pquad #dataset-squad_v2 #license-mit #endpoints_compatible #region-us 




# xlm-roberta-base-finetuned-pquad-squad

This model is a version of 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
# xlm-roberta-base-finetuned-pquad-squad

This model is a version of 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
TAGS
#transformers #pytorch #tensorboard #xlm-roberta #question-answering #generated_from_trainer #en #fa #dataset-Gholamreza/pquad #dataset-squad_v2 #license-mit #endpoints_compatible #region-us 
 # xlm-roberta-base-finetuned-pquad-squad

This model is a version of 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
TAGS
#transformers #pytorch #tensorboard #xlm-roberta #question-answering #generated_from_trainer #en #fa #dataset-Gholamreza/pquad #dataset-squad_v2 #license-mit #endpoints_compatible #region-us 
# xlm-roberta-base-finetuned-pquad-squad

This model is a version of 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