pytorch roberta text-classification unk dataset:vlsb/autotrain-data-security-texts-classification-distilroberta transformers autotrain co2_eq_emissions
---
tags: autotrain
language: unk
widget:
- text: "I love AutoTrain 🤗"
datasets:
- vlsb/autotrain-data-security-texts-classification-distilroberta
co2_eq_emissions: 2.0817207656772445
---

# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 688220764
- CO2 Emissions (in grams): 2.0817207656772445

## Validation Metrics

- Loss: 0.3055502772331238
- Accuracy: 0.9030612244897959
- Precision: 0.9528301886792453
- Recall: 0.8782608695652174
- AUC: 0.9439076757917337
- F1: 0.9140271493212669

## Usage

You can use cURL to access this model:

```
$ curl -X POST -H "Authorization: Bearer YOUR_API_KEY" -H "Content-Type: application/json" -d '{"inputs": "I love AutoTrain"}' https://api-inference.huggingface.co/models/vlsb/autotrain-security-texts-classification-distilroberta-688220764
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("vlsb/autotrain-security-texts-classification-distilroberta-688220764", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("vlsb/autotrain-security-texts-classification-distilroberta-688220764", use_auth_token=True)

inputs = tokenizer("I love AutoTrain", return_tensors="pt")

outputs = model(**inputs)
```