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---
tags: autonlp
language: en
widget:
- text: "I love AutoNLP 🤗"
datasets:
- amansolanki/autonlp-data-Tweet-Sentiment-Extraction
co2_eq_emissions: 3.651199395353127
---
# Model Trained Using AutoNLP
- Problem type: Multi-class Classification
- Model ID: 20114061
- CO2 Emissions (in grams): 3.651199395353127
## Validation Metrics
- Loss: 0.5046541690826416
- Accuracy: 0.8036219581211093
- Macro F1: 0.807095210403678
- Micro F1: 0.8036219581211093
- Weighted F1: 0.8039634739225368
- Macro Precision: 0.8076842795233988
- Micro Precision: 0.8036219581211093
- Weighted Precision: 0.8052135235094771
- Macro Recall: 0.8075241470527056
- Micro Recall: 0.8036219581211093
- Weighted Recall: 0.8036219581211093
## 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 AutoNLP"}' https://api-inference.huggingface.co/models/amansolanki/autonlp-Tweet-Sentiment-Extraction-20114061
```
Or Python API:
```
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("amansolanki/autonlp-Tweet-Sentiment-Extraction-20114061", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("amansolanki/autonlp-Tweet-Sentiment-Extraction-20114061", use_auth_token=True)
inputs = tokenizer("I love AutoNLP", return_tensors="pt")
outputs = model(**inputs)
``` |