anger fear sadness surprise
---
tags: autotrain
language: unk
widget:
- text: "I love AutoTrain 🤗"
datasets:
- crcb/autotrain-data-carer_new
co2_eq_emissions: 3.9861818439722594
---

# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 781623992
- CO2 Emissions (in grams): 3.9861818439722594

## Validation Metrics

- Loss: 0.1639203429222107
- Accuracy: 0.9389179755671903
- Macro F1: 0.9055551236566716
- Micro F1: 0.9389179755671903
- Weighted F1: 0.9379300009988988
- Macro Precision: 0.9466951148514304
- Micro Precision: 0.9389179755671903
- Weighted Precision: 0.9435523016000105
- Macro Recall: 0.8818551804621082
- Micro Recall: 0.9389179755671903
- Weighted Recall: 0.9389179755671903


## 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-carer_new-781623992
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("crcb/autotrain-carer_new-781623992", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("crcb/autotrain-carer_new-781623992", use_auth_token=True)

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

outputs = model(**inputs)
```