
# Overview
This model is an experiment I and my friend did as a researcher internship at the National University of Singapore (NUS). We finetuned the model to our datasets in Finance and Healthcare domain, in the Malay Language.

# Details
- Finetuned from the base model by [timpal0l](https://huggingface.co/timpal0l/mdeberta-v3-base-squad2)
- The base datasets from [SQuAD2.0](https://rajpurkar.github.io/SQuAD-explorer/)
- Our [datasets](https://ids.nus.edu.sg/microsites/nzsg-nlp/datahub.html) in Finance and Healthcare domain

# Finetuned Detail
```py
from transformers import TrainingArguments

training_args = TrainingArguments(
    output_dir='test_trainer', 
    evaluation_strategy='epoch', 
    num_train_epochs=20, 
    optim='adamw_torch',
    report_to='all',
    logging_steps=1,
)
```

# How to use the Model
```py
from transformers import AutoModelForQuestionAnswering, AutoTokenizer, pipeline

model_name = "primasr/multilingualbert-for-eqa-finetuned"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForQuestionAnswering.from_pretrained(model_name)
nlp = pipeline("question-answering", model=model, tokenizer=tokenizer)
```
{"language": ["ms"], "datasets": ["squad_v2"], "metrics": ["exact_match", "f1"]}
transformers pytorch deberta-v2 question-answering ms dataset:squad_v2 endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #deberta-v2 #question-answering #ms #dataset-squad_v2 #endpoints_compatible #has_space #region-us 


# Overview
This model is an experiment I and my friend did as a researcher internship at the National University of Singapore (NUS). We finetuned the model to our datasets in Finance and Healthcare domain, in the Malay Language.

# Details
- Finetuned from the base model by timpal0l
- The base datasets from SQuAD2.0
- Our datasets in Finance and Healthcare domain

# Finetuned Detail


# How to use the Model

# Overview
This model is an experiment I and my friend did as a researcher internship at the National University of Singapore (NUS). We finetuned the model to our datasets in Finance and Healthcare domain, in the Malay Language. # Details
- Finetuned from the base model by timpal0l
- The base datasets from SQuAD2.0
- Our datasets in Finance and Healthcare domain # Finetuned Detail # How to use the Model
TAGS
#transformers #pytorch #deberta-v2 #question-answering #ms #dataset-squad_v2 #endpoints_compatible #has_space #region-us 
 # Overview
This model is an experiment I and my friend did as a researcher internship at the National University of Singapore (NUS). We finetuned the model to our datasets in Finance and Healthcare domain, in the Malay Language. # Details
- Finetuned from the base model by timpal0l
- The base datasets from SQuAD2.0
- Our datasets in Finance and Healthcare domain # Finetuned Detail # How to use the Model
TAGS
#transformers #pytorch #deberta-v2 #question-answering #ms #dataset-squad_v2 #endpoints_compatible #has_space #region-us 
# Overview
This model is an experiment I and my friend did as a researcher internship at the National University of Singapore (NUS). We finetuned the model to our datasets in Finance and Healthcare domain, in the Malay Language.# Details
- Finetuned from the base model by timpal0l
- The base datasets from SQuAD2.0
- Our datasets in Finance and Healthcare domain# Finetuned Detail# How to use the Model