anger disgust fear guilt joy sadness shame
---
tags: autotrain
language: unk
widget:
- text: "I love AutoTrain 🤗"
datasets:
- crcb/autotrain-data-isear_bert
co2_eq_emissions: 0.026027055434994496
---

# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 786224257
- CO2 Emissions (in grams): 0.026027055434994496

## Validation Metrics

- Loss: 0.8348872065544128
- Accuracy: 0.7272727272727273
- Macro F1: 0.7230931630686932
- Micro F1: 0.7272727272727273
- Weighted F1: 0.7236599456423468
- Macro Precision: 0.7328252157220334
- Micro Precision: 0.7272727272727273
- Weighted Precision: 0.7336599708829821
- Macro Recall: 0.7270448163292604
- Micro Recall: 0.7272727272727273
- Weighted Recall: 0.7272727272727273


## 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-isear_bert-786224257
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("crcb/autotrain-isear_bert-786224257", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("crcb/autotrain-isear_bert-786224257", use_auth_token=True)

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

outputs = model(**inputs)
```