# Model Card for Password-Model

 
# Model Details
 
## Model Description
 
 
The Password Model is intended to be used with [Credential Digger](https://github.com/SAP/credential-digger) in order to automatically filter false positive password discoveries.
 
- **Developed by:** SAP OSS
- **Shared by [Optional]:** Hugging Face
- **Model type:** Text Classification
- **Language(s) (NLP):** en
- **License:** Apache-2.0
- **Related Models:** 
  - **Parent Model:** RoBERTa
- **Resources for more information:**
  - [GitHub Repo](https://github.com/SAP/credential-digger) 
  - [Associated Paper](https://www.scitepress.org/Papers/2021/102381/102381.pdf) 
 
# Uses
 
 
## Direct Use
The model is directly integrated into [Credential Digger]((https://github.com/SAP/credential-digger) and can be used to filter the false positive password discoveries of a scan.
 

## Out-of-Scope Use
 
The model should not be used to intentionally create hostile or alienating environments for people. 
 
 
# Training Details
 
## Training Data
 
[CodeBERT-base-mlm](https://huggingface.co/microsoft/codebert-base-mlm) fine-tuned on a dataset for leak detection.
 
 
## Training Procedure
 
 
### Preprocessing
 
More information needed
 
### Speeds, Sizes, Times
 
More information needed
 
# Evaluation
 
More information needed
 
## Testing Data, Factors & Metrics
 
### Testing Data
 
More information needed
 
### Factors
 
More information needed
 
### Metrics
 
More information needed
 
## Results 
 
More information needed
 
 
# Model Examination
More information needed
 
# Environmental Impact
 
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
 
- **Hardware Type:** More information needed
- **Hours used:** More information needed
- **Cloud Provider:** More information needed
- **Compute Region:** More information needed
- **Carbon Emitted:** More information needed
 
# Technical Specifications [optional]
 
## Model Architecture and Objective
 
More information needed
 
## Compute Infrastructure
More information needed
 
### Hardware
 
More information needed
 
### Software
 
More information needed
 
 
# Citation
 
**BibTeX:**
 
```
TBD
```
 
# Model Card Authors [optional]
 
SAP OSS in collaboration with Ezi Ozoani and the Hugging Face team.
 
# Model Card Contact
 
More information needed

# How to Get Started with the Model
 
The model is directly integrated into Credential Digger and can be used to filter the false positive discoveries of a scan
 
<details>
<summary> Click to expand </summary>

```python
from transformers import AutoTokenizer, AutoModelForSequenceClassification
 
tokenizer = AutoTokenizer.from_pretrained("SAPOSS/password-model")
 
model = AutoModelForSequenceClassification.from_pretrained("SAPOSS/password-model")
 
 ```
</details>

{"language": ["en"]}
transformers tf roberta text-classification en arxiv:1910.09700 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #tf #roberta #text-classification #en #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #region-us 

# Model Card for Password-Model

 
# Model Details
 
## Model Description
 
 
The Password Model is intended to be used with Credential Digger in order to automatically filter false positive password discoveries.
 
- Developed by: SAP OSS
- Shared by [Optional]: Hugging Face
- Model type: Text Classification
- Language(s) (NLP): en
- License: Apache-2.0
- Related Models: 
  - Parent Model: RoBERTa
- Resources for more information:
  - GitHub Repo 
  - Associated Paper 
 
# Uses
 
 
## Direct Use
The model is directly integrated into Credential Digger and can be used to filter the false positive password discoveries of a scan.
 

## Out-of-Scope Use
 
The model should not be used to intentionally create hostile or alienating environments for people. 
 
 
# Training Details
 
## Training Data
 
CodeBERT-base-mlm fine-tuned on a dataset for leak detection.
 
 
## Training Procedure
 
 
### Preprocessing
 
More information needed
 
### Speeds, Sizes, Times
 
More information needed
 
# Evaluation
 
More information needed
 
## Testing Data, Factors & Metrics
 
### Testing Data
 
More information needed
 
### Factors
 
More information needed
 
### Metrics
 
More information needed
 
## Results 
 
More information needed
 
 
# Model Examination
More information needed
 
# Environmental Impact
 
Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
 
- Hardware Type: More information needed
- Hours used: More information needed
- Cloud Provider: More information needed
- Compute Region: More information needed
- Carbon Emitted: More information needed
 
# Technical Specifications [optional]
 
## Model Architecture and Objective
 
More information needed
 
## Compute Infrastructure
More information needed
 
### Hardware
 
More information needed
 
### Software
 
More information needed
 
 
BibTeX:
 

 
# Model Card Authors [optional]
 
SAP OSS in collaboration with Ezi Ozoani and the Hugging Face team.
 
# Model Card Contact
 
More information needed

# How to Get Started with the Model
 
The model is directly integrated into Credential Digger and can be used to filter the false positive discoveries of a scan
 
<details>
<summary> Click to expand </summary>


</details>

# Model Card for Password-Model # Model Details ## Model Description
 
 
The Password Model is intended to be used with Credential Digger in order to automatically filter false positive password discoveries.
 
- Developed by: SAP OSS
- Shared by [Optional]: Hugging Face
- Model type: Text Classification
- Language(s) (NLP): en
- License: Apache-2.0
- Related Models: 
  - Parent Model: RoBERTa
- Resources for more information:
  - GitHub Repo 
  - Associated Paper # Uses ## Direct Use
The model is directly integrated into Credential Digger and can be used to filter the false positive password discoveries of a scan. ## Out-of-Scope Use
 
The model should not be used to intentionally create hostile or alienating environments for people. # Training Details ## Training Data
 
CodeBERT-base-mlm fine-tuned on a dataset for leak detection. ## Training Procedure ### Preprocessing
 
More information needed ### Speeds, Sizes, Times
 
More information needed # Evaluation
 
More information needed ## Testing Data, Factors & Metrics ### Testing Data
 
More information needed ### Factors
 
More information needed ### Metrics
 
More information needed ## Results 
 
More information needed # Model Examination
More information needed # Environmental Impact
 
Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
 
- Hardware Type: More information needed
- Hours used: More information needed
- Cloud Provider: More information needed
- Compute Region: More information needed
- Carbon Emitted: More information needed # Technical Specifications [optional] ## Model Architecture and Objective
 
More information needed ## Compute Infrastructure
More information needed ### Hardware
 
More information needed ### Software
 
More information needed
 
 
BibTeX: # Model Card Authors [optional]
 
SAP OSS in collaboration with Ezi Ozoani and the Hugging Face team. # Model Card Contact
 
More information needed # How to Get Started with the Model
 
The model is directly integrated into Credential Digger and can be used to filter the false positive discoveries of a scan
 
<details>
<summary> Click to expand </summary>


</details>
TAGS
#transformers #tf #roberta #text-classification #en #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #region-us 
 # Model Card for Password-Model # Model Details ## Model Description
 
 
The Password Model is intended to be used with Credential Digger in order to automatically filter false positive password discoveries.
 
- Developed by: SAP OSS
- Shared by [Optional]: Hugging Face
- Model type: Text Classification
- Language(s) (NLP): en
- License: Apache-2.0
- Related Models: 
  - Parent Model: RoBERTa
- Resources for more information:
  - GitHub Repo 
  - Associated Paper # Uses ## Direct Use
The model is directly integrated into Credential Digger and can be used to filter the false positive password discoveries of a scan. ## Out-of-Scope Use
 
The model should not be used to intentionally create hostile or alienating environments for people. # Training Details ## Training Data
 
CodeBERT-base-mlm fine-tuned on a dataset for leak detection. ## Training Procedure ### Preprocessing
 
More information needed ### Speeds, Sizes, Times
 
More information needed # Evaluation
 
More information needed ## Testing Data, Factors & Metrics ### Testing Data
 
More information needed ### Factors
 
More information needed ### Metrics
 
More information needed ## Results 
 
More information needed # Model Examination
More information needed # Environmental Impact
 
Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
 
- Hardware Type: More information needed
- Hours used: More information needed
- Cloud Provider: More information needed
- Compute Region: More information needed
- Carbon Emitted: More information needed # Technical Specifications [optional] ## Model Architecture and Objective
 
More information needed ## Compute Infrastructure
More information needed ### Hardware
 
More information needed ### Software
 
More information needed
 
 
BibTeX: # Model Card Authors [optional]
 
SAP OSS in collaboration with Ezi Ozoani and the Hugging Face team. # Model Card Contact
 
More information needed # How to Get Started with the Model
 
The model is directly integrated into Credential Digger and can be used to filter the false positive discoveries of a scan
 
<details>
<summary> Click to expand </summary>


</details>
TAGS
#transformers #tf #roberta #text-classification #en #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #region-us 
# Model Card for Password-Model# Model Details## Model Description
 
 
The Password Model is intended to be used with Credential Digger in order to automatically filter false positive password discoveries.
 
- Developed by: SAP OSS
- Shared by [Optional]: Hugging Face
- Model type: Text Classification
- Language(s) (NLP): en
- License: Apache-2.0
- Related Models: 
  - Parent Model: RoBERTa
- Resources for more information:
  - GitHub Repo 
  - Associated Paper# Uses## Direct Use
The model is directly integrated into Credential Digger and can be used to filter the false positive password discoveries of a scan.## Out-of-Scope Use
 
The model should not be used to intentionally create hostile or alienating environments for people.# Training Details## Training Data
 
CodeBERT-base-mlm fine-tuned on a dataset for leak detection.## Training Procedure### Preprocessing
 
More information needed### Speeds, Sizes, Times
 
More information needed# Evaluation
 
More information needed## Testing Data, Factors & Metrics### Testing Data
 
More information needed### Factors
 
More information needed### Metrics
 
More information needed## Results 
 
More information needed# Model Examination
More information needed# Environmental Impact
 
Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
 
- Hardware Type: More information needed
- Hours used: More information needed
- Cloud Provider: More information needed
- Compute Region: More information needed
- Carbon Emitted: More information needed# Technical Specifications [optional]## Model Architecture and Objective
 
More information needed## Compute Infrastructure
More information needed### Hardware
 
More information needed### Software
 
More information needed
 
 
BibTeX:# Model Card Authors [optional]
 
SAP OSS in collaboration with Ezi Ozoani and the Hugging Face team.# Model Card Contact
 
More information needed# How to Get Started with the Model
 
The model is directly integrated into Credential Digger and can be used to filter the false positive discoveries of a scan
 
<details>
<summary> Click to expand </summary>


</details>