negative positive
---
tags: autotrain
language: en
widget:
- text: "I love AutoTrain 🤗"
datasets:
- deepesh0x/autotrain-data-mlsec
co2_eq_emissions: 33.183779535405364
---

# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 1013333726
- CO2 Emissions (in grams): 33.183779535405364

## Validation Metrics

- Loss: 0.1998898833990097
- Accuracy: 0.9226923076923077
- Precision: 0.9269808389435525
- Recall: 0.9177134068187645
- AUC: 0.9785380985232148
- F1: 0.9223238438747907

## 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/deepesh0x/autotrain-mlsec-1013333726
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("deepesh0x/autotrain-mlsec-1013333726", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("deepesh0x/autotrain-mlsec-1013333726", use_auth_token=True)

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

outputs = model(**inputs)
```