---
tags:
- autotrain
- text-classification
language:
- unk
widget:
- text: "I love AutoTrain"
datasets:
- SH-W/autotrain-data-5000_koi
co2_eq_emissions:
  emissions: 3.920765439350259
---

# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 77927140735
- CO2 Emissions (in grams): 3.9208

## Validation Metrics

- Loss: 2.432
- Accuracy: 0.415
- Macro F1: 0.410
- Micro F1: 0.415
- Weighted F1: 0.410
- Macro Precision: 0.459
- Micro Precision: 0.415
- Weighted Precision: 0.456
- Macro Recall: 0.413
- Micro Recall: 0.415
- Weighted Recall: 0.415


## 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/SH-W/autotrain-5000_koi-77927140735
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("SH-W/autotrain-5000_koi-77927140735", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("SH-W/autotrain-5000_koi-77927140735", use_auth_token=True)

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

outputs = model(**inputs)
```