anger fear sadness surprise
---
tags: autotrain
language: en
widget:
- text: "I love AutoTrain 🤗"
datasets:
- crcb/autotrain-data-emo_carer_nojoylove
co2_eq_emissions: 2.370895196595982
---

# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 751422974
- CO2 Emissions (in grams): 2.370895196595982

## Validation Metrics

- Loss: 0.15362708270549774
- Accuracy: 0.9345549738219895
- Macro F1: 0.9016011681330569
- Micro F1: 0.9345549738219895
- Weighted F1: 0.9345413976263288
- Macro Precision: 0.9032333514618506
- Micro Precision: 0.9345549738219895
- Weighted Precision: 0.9345804677958041
- Macro Recall: 0.9001021129974442
- Micro Recall: 0.9345549738219895
- Weighted Recall: 0.9345549738219895


## 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-751422974
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("crcb/autotrain-emo_carer_nojoylove-751422974", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("crcb/autotrain-emo_carer_nojoylove-751422974", use_auth_token=True)

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

outputs = model(**inputs)
```