anger fear sadness surprise
---
tags: autotrain
language: en
widget:
- text: "I love AutoTrain 🤗"
datasets:
- crcb/autotrain-data-emo_carer_nojoylove
co2_eq_emissions: 12.236769332727217
---

# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 751422966
- CO2 Emissions (in grams): 12.236769332727217

## Validation Metrics

- Loss: 0.1358409821987152
- Accuracy: 0.9397905759162304
- Macro F1: 0.9096049124431982
- Micro F1: 0.9397905759162304
- Weighted F1: 0.9395954853807672
- Macro Precision: 0.919807346649452
- Micro Precision: 0.9397905759162304
- Weighted Precision: 0.9407259082357824
- Macro Recall: 0.9024000547645126
- Micro Recall: 0.9397905759162304
- Weighted Recall: 0.9397905759162304


## 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/crcb/autotrain-emo_carer_nojoylove-751422966
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("crcb/autotrain-emo_carer_nojoylove-751422966", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("crcb/autotrain-emo_carer_nojoylove-751422966", use_auth_token=True)

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

outputs = model(**inputs)
```