---
tags:
- autotrain
- text-classification
language:
- unk
widget:
- text: "I love AutoTrain 🤗"
datasets:
- bbiasi/autotrain-data-sentimental_analysis_bit
co2_eq_emissions:
  emissions: 0.006100220390969195
---

# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 51605122225
- CO2 Emissions (in grams): 0.0061

## Validation Metrics

- Loss: 0.370
- Accuracy: 0.826
- Precision: 0.845
- Recall: 0.920
- AUC: 0.899
- F1: 0.880

## 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/bbiasi/autotrain-sentimental_analysis_bit-51605122225
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("bbiasi/autotrain-sentimental_analysis_bit-51605122225", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("bbiasi/autotrain-sentimental_analysis_bit-51605122225", use_auth_token=True)

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

outputs = model(**inputs)
```