README.md

---
tags:
- autotrain
- text-classification
language:
- en
widget:
- text: "I love AutoTrain 🤗"
datasets:
- lucieackley/autotrain-data-multi_msg_4
co2_eq_emissions:
  emissions: 1.531642698505257
---

# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 2799882586
- CO2 Emissions (in grams): 1.5316

## Validation Metrics

- Loss: 0.251
- Accuracy: 0.950
- Macro F1: 0.949
- Micro F1: 0.950
- Weighted F1: 0.950
- Macro Precision: 0.962
- Micro Precision: 0.950
- Weighted Precision: 0.953
- Macro Recall: 0.938
- Micro Recall: 0.950
- Weighted Recall: 0.950


## 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/lucieackley/autotrain-multi_msg_4-2799882586
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("lucieackley/autotrain-multi_msg_4-2799882586", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("lucieackley/autotrain-multi_msg_4-2799882586", use_auth_token=True)

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

outputs = model(**inputs)
```