# Model Card for Model ID

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This modelcard aims to be text classification for research abstract regarding to disaster management phase.
## Model Details

### Model Description

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- **Developed by:** Odirunia
- **Shared by [optional]:** [More Information Needed]
- **Model type:** Bert
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
- **Finetuned from model [optional]:** [More Information Needed]

### Model Sources [optional]

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- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]

## Uses

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### Direct Use

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### Downstream Use [optional]

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[More Information Needed]

### Out-of-Scope Use

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## Bias, Risks, and Limitations

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### Recommendations

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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.

## How to Get Started with the Model

Use the code below to get started with the model.

[More Information Needed]

## Training Details

### Training Data

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### Training Procedure 

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#### Preprocessing [optional]

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{"language": ["id", "en"], "license": "apache-2.0", "library_name": "transformers", "tags": ["bert", "research abstract"], "metrics": [{"name": "accuracy", "value": 0.9394}, {"name": "precision", "value": 0.9413}, {"name": "recall", "value": 0.9394}, {"name": "F1-Score", "value": 0.9388}], "pipeline_tag": "text-classification", "widget": [{"text": "Following the tsunami in December 2004 in Aceh, Indonesia, there has been a massive programme of rebuilding permanent houses for the tsunami victims. The houses are of various designs, and the internal conditions and thermal performance vary considerably. This paper is aimed at assessing comfort in a number of these houses, and is based on measurements from ten designs of post tsunami houses conducted between 22nd May and 4th July 2009. These ten house types are categorized by different form, design and materials, two houses of each type being represented in the results. Air and surface temperatures, relative humidity, and air velocity were measured and questionnaires on thermal comfort were filled in by the occupants. The results show an interesting range of temperature and humidity, ranging from 250C-380C indoors and 210C-41.40C outdoors, relative humidity of 40%-86% indoors, compared with 26%-98% outdoors. The households qualify their house comfort by voting seven thermal sensation scales.", "example_title": "recovery"}]}
transformers bert research abstract text-classification id en license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #bert #research abstract #text-classification #id #en #license-apache-2.0 #endpoints_compatible #region-us 

# Model Card for Model ID



This modelcard aims to be text classification for research abstract regarding to disaster management phase.
## Model Details

### Model Description





- Developed by: Odirunia
- Shared by [optional]: 
- Model type: Bert
- Language(s) (NLP): 
- License: 
- Finetuned from model [optional]: 

### Model Sources [optional]



- Repository: 
- Paper [optional]: 
- Demo [optional]: 

## Uses



### Direct Use





### Downstream Use [optional]





### Out-of-Scope Use





## Bias, Risks, and Limitations





### Recommendations



Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.

## How to Get Started with the Model

Use the code below to get started with the model.



## Training Details

### Training Data





### Training Procedure 



#### Preprocessing [optional]


# Model Card for Model ID



This modelcard aims to be text classification for research abstract regarding to disaster management phase. ## Model Details ### Model Description





- Developed by: Odirunia
- Shared by [optional]: 
- Model type: Bert
- Language(s) (NLP): 
- License: 
- Finetuned from model [optional]: ### Model Sources [optional]



- Repository: 
- Paper [optional]: 
- Demo [optional]: ## Uses ### Direct Use ### Downstream Use [optional] ### Out-of-Scope Use ## Bias, Risks, and Limitations ### Recommendations



Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model

Use the code below to get started with the model. ## Training Details ### Training Data ### Training Procedure #### Preprocessing [optional]
TAGS
#transformers #bert #research abstract #text-classification #id #en #license-apache-2.0 #endpoints_compatible #region-us 
 # Model Card for Model ID



This modelcard aims to be text classification for research abstract regarding to disaster management phase. ## Model Details ### Model Description





- Developed by: Odirunia
- Shared by [optional]: 
- Model type: Bert
- Language(s) (NLP): 
- License: 
- Finetuned from model [optional]: ### Model Sources [optional]



- Repository: 
- Paper [optional]: 
- Demo [optional]: ## Uses ### Direct Use ### Downstream Use [optional] ### Out-of-Scope Use ## Bias, Risks, and Limitations ### Recommendations



Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model

Use the code below to get started with the model. ## Training Details ### Training Data ### Training Procedure #### Preprocessing [optional]