---
tags:
- autotrain
- text-classification
language:
- en
widget:
- text: "I love AutoTrain 🤗"
datasets:
- rahulmallah/autotrain-data-emotion-detection
co2_eq_emissions:
  emissions: 0.037160667072201545
---

# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 1366352626
- CO2 Emissions (in grams): 0.0372

## Validation Metrics

- Loss: 1.772
- Accuracy: 0.394
- Macro F1: 0.197
- Micro F1: 0.394
- Weighted F1: 0.351
- Macro Precision: 0.217
- Micro Precision: 0.394
- Weighted Precision: 0.345
- Macro Recall: 0.213
- Micro Recall: 0.394
- Weighted Recall: 0.394


## 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/rahulmallah/autotrain-emotion-detection-1366352626
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("rahulmallah/autotrain-emotion-detection-1366352626", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("rahulmallah/autotrain-emotion-detection-1366352626", use_auth_token=True)

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

outputs = model(**inputs)
```