README.md

---
tags:
- autotrain
- text-classification
language:
- it
widget:
- text: "I love AutoTrain 🤗"
datasets:
- davanstrien/autotrain-data-cultural_heritage_metadata_accuracy
co2_eq_emissions:
  emissions: 7.171395981202868
---

# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 48840118272
- CO2 Emissions (in grams): 7.1714

## Validation Metrics

- Loss: 0.085
- Accuracy: 0.972
- Macro F1: 0.972
- Micro F1: 0.972
- Weighted F1: 0.972
- Macro Precision: 0.972
- Micro Precision: 0.972
- Weighted Precision: 0.972
- Macro Recall: 0.972
- Micro Recall: 0.972
- Weighted Recall: 0.972


## 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"}' /static-proxy?url=https%3A%2F%2Fapi-inference.huggingface.co%2Fmodels%2Fdavanstrien%2Fautotrain-cultural_heritage_metadata_accuracy-48840118272%3C%2Fspan%3E
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("davanstrien/autotrain-cultural_heritage_metadata_accuracy-48840118272", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("davanstrien/autotrain-cultural_heritage_metadata_accuracy-48840118272", use_auth_token=True)

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

outputs = model(**inputs)
```