# Model Card for Model ID

<!-- Provide a quick summary of what the model is/does. -->


## Model Details

### Model Description

- Model to extract Relations from cyber threat intelligence(CTI) text.
- Standalone Model: 


- **Developed by:** Leon Lukas

- **Model type:** seq2seq
- **Language(s) (NLP): English
- **Finetuned from model : mrmoor/cti-t5-RE-NYT (T5 model trained on NYT RE)

### Metrics test set

- precision: 0.3141203703703703
- recall:  0.37442129629629634,
- f1 : 0.34163032380169717

### Model Sources [optional]

<!-- Provide the basic links for the model. -->

- **Repository:** https://github.com/l0renor/Relation-Extraction-and-Knowledge-Graph-Generation-on-MISP-Event-Reports
- **Paper [optional]:** https://github.com/l0renor/Relation-Extraction-and-Knowledge-Graph-Generation-on-MISP-Event-Reports
{"tags": ["STIX", "NER", "RE", "CTI", "cyber threat intelligence"], "metrics": [{"f1": 0.34163032380169717}, {"recall": 0.37442129629629634}, {"precision": 0.3141203703703703}], "pipeline_tag": "text2text-generation"}
transformers pytorch t5 text2text-generation STIX NER RE CTI cyber threat intelligence autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #t5 #text2text-generation #STIX #NER #RE #CTI #cyber threat intelligence #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

# Model Card for Model ID




## Model Details

### Model Description

- Model to extract Relations from cyber threat intelligence(CTI) text.
- Standalone Model: 


- Developed by: Leon Lukas

- Model type: seq2seq
- Language(s) (NLP): English
- Finetuned from model : mrmoor/cti-t5-RE-NYT (T5 model trained on NYT RE)

### Metrics test set

- precision: 0.3141203703703703
- recall:  0.37442129629629634,
- f1 : 0.34163032380169717

### Model Sources [optional]



- Repository: URL
- Paper [optional]: URL
# Model Card for Model ID ## Model Details ### Model Description

- Model to extract Relations from cyber threat intelligence(CTI) text.
- Standalone Model: 


- Developed by: Leon Lukas

- Model type: seq2seq
- Language(s) (NLP): English
- Finetuned from model : mrmoor/cti-t5-RE-NYT (T5 model trained on NYT RE) ### Metrics test set

- precision: 0.3141203703703703
- recall:  0.37442129629629634,
- f1 : 0.34163032380169717 ### Model Sources [optional]



- Repository: URL
- Paper [optional]: URL
TAGS
#transformers #pytorch #t5 #text2text-generation #STIX #NER #RE #CTI #cyber threat intelligence #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 # Model Card for Model ID ## Model Details ### Model Description

- Model to extract Relations from cyber threat intelligence(CTI) text.
- Standalone Model: 


- Developed by: Leon Lukas

- Model type: seq2seq
- Language(s) (NLP): English
- Finetuned from model : mrmoor/cti-t5-RE-NYT (T5 model trained on NYT RE) ### Metrics test set

- precision: 0.3141203703703703
- recall:  0.37442129629629634,
- f1 : 0.34163032380169717 ### Model Sources [optional]



- Repository: URL
- Paper [optional]: URL
TAGS
#transformers #pytorch #t5 #text2text-generation #STIX #NER #RE #CTI #cyber threat intelligence #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
# Model Card for Model ID## Model Details### Model Description

- Model to extract Relations from cyber threat intelligence(CTI) text.
- Standalone Model: 


- Developed by: Leon Lukas

- Model type: seq2seq
- Language(s) (NLP): English
- Finetuned from model : mrmoor/cti-t5-RE-NYT (T5 model trained on NYT RE)### Metrics test set

- precision: 0.3141203703703703
- recall:  0.37442129629629634,
- f1 : 0.34163032380169717### Model Sources [optional]



- Repository: URL
- Paper [optional]: URL