negative positive
---
tags: autotrain
language: en
widget:
- text: "I love AutoTrain 🤗"
datasets:
- deepesh0x/autotrain-data-GlueModels
co2_eq_emissions: 60.24263131580023
---

# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 1010733562
- CO2 Emissions (in grams): 60.24263131580023

## Validation Metrics

- Loss: 0.1812974065542221
- Accuracy: 0.9252564102564103
- Precision: 0.9409888357256778
- Recall: 0.9074596257369905
- AUC: 0.9809618001947271
- F1: 0.923920135717082

## 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-GlueModels-1010733562
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("deepesh0x/autotrain-GlueModels-1010733562", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("deepesh0x/autotrain-GlueModels-1010733562", use_auth_token=True)

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

outputs = model(**inputs)
```