---
tags: autonlp
language: en
widget:
- text: "I love AutoNLP 🤗"
datasets:
- akilesh96/autonlp-data-mrcooper_text_classification
co2_eq_emissions: 5.999771405025692
---

# Model Trained Using AutoNLP

- Problem type: Multi-class Classification
- Model ID: 529614927
- CO2 Emissions (in grams): 5.999771405025692

## Validation Metrics

- Loss: 0.7582379579544067
- Accuracy: 0.7636103151862464
- Macro F1: 0.770630619486531
- Micro F1: 0.7636103151862464
- Weighted F1: 0.765233270165301
- Macro Precision: 0.7746285216467107
- Micro Precision: 0.7636103151862464
- Weighted Precision: 0.7683270753840836
- Macro Recall: 0.7680576576961138
- Micro Recall: 0.7636103151862464
- Weighted Recall: 0.7636103151862464


## 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/akilesh96/autonlp-mrcooper_text_classification-529614927
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("akilesh96/autonlp-mrcooper_text_classification-529614927", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("akilesh96/autonlp-mrcooper_text_classification-529614927", use_auth_token=True)

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

outputs = model(**inputs)
```