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# thai-squad

This model is a fine-tuned version of [deepset/xlm-roberta-base-squad2](https://huggingface.co/deepset/xlm-roberta-base-squad2) on Thai dataset from [iApp Technology Co., Ltd.](https://github.com/iapp-technology/iapp-wiki-qa-dataset).

## Intended uses & limitations

This model intends to use with Thai question and answering task

## Training and evaluation data

Trained and evaluated by [iApp Technology Co., Ltd.](https://github.com/iapp-technology/iapp-wiki-qa-dataset) dataset.

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 3e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2

## Performance
Evaluated on the SQuAD 1.0 test dataset
```
"exact": 62.51728907330567
"f1": 73.62388955749958
"total": 723
```

### Framework versions

- Transformers 4.11.3
- Pytorch 1.9.0+cu111
- Datasets 1.14.0
- Tokenizers 0.10.3

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transformers pytorch tensorboard xlm-roberta question-answering generated_from_trainer th license:cc-by-4.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #xlm-roberta #question-answering #generated_from_trainer #th #license-cc-by-4.0 #endpoints_compatible #region-us 




# thai-squad

This model is a fine-tuned version of deepset/xlm-roberta-base-squad2 on Thai dataset from iApp Technology Co., Ltd..

## Intended uses & limitations

This model intends to use with Thai question and answering task

## Training and evaluation data

Trained and evaluated by iApp Technology Co., Ltd. dataset.

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 3e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2

## Performance
Evaluated on the SQuAD 1.0 test dataset


### Framework versions

- Transformers 4.11.3
- Pytorch 1.9.0+cu111
- Datasets 1.14.0
- Tokenizers 0.10.3

# thai-squad

This model is a fine-tuned version of deepset/xlm-roberta-base-squad2 on Thai dataset from iApp Technology Co., Ltd.. ## Intended uses & limitations

This model intends to use with Thai question and answering task ## Training and evaluation data

Trained and evaluated by iApp Technology Co., Ltd. dataset. ## Training procedure ### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 3e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2 ## Performance
Evaluated on the SQuAD 1.0 test dataset ### Framework versions

- Transformers 4.11.3
- Pytorch 1.9.0+cu111
- Datasets 1.14.0
- Tokenizers 0.10.3
TAGS
#transformers #pytorch #tensorboard #xlm-roberta #question-answering #generated_from_trainer #th #license-cc-by-4.0 #endpoints_compatible #region-us 
 # thai-squad

This model is a fine-tuned version of deepset/xlm-roberta-base-squad2 on Thai dataset from iApp Technology Co., Ltd.. ## Intended uses & limitations

This model intends to use with Thai question and answering task ## Training and evaluation data

Trained and evaluated by iApp Technology Co., Ltd. dataset. ## Training procedure ### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 3e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2 ## Performance
Evaluated on the SQuAD 1.0 test dataset ### Framework versions

- Transformers 4.11.3
- Pytorch 1.9.0+cu111
- Datasets 1.14.0
- Tokenizers 0.10.3
TAGS
#transformers #pytorch #tensorboard #xlm-roberta #question-answering #generated_from_trainer #th #license-cc-by-4.0 #endpoints_compatible #region-us 
# thai-squad

This model is a fine-tuned version of deepset/xlm-roberta-base-squad2 on Thai dataset from iApp Technology Co., Ltd..## Intended uses & limitations

This model intends to use with Thai question and answering task## Training and evaluation data

Trained and evaluated by iApp Technology Co., Ltd. dataset.## Training procedure### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 3e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2## Performance
Evaluated on the SQuAD 1.0 test dataset### Framework versions

- Transformers 4.11.3
- Pytorch 1.9.0+cu111
- Datasets 1.14.0
- Tokenizers 0.10.3