---
tags: autotrain
language: en
widget:
- text: "I love AutoTrain 🤗"
datasets:
- ndavid/autotrain-data-trec-fine-bert
co2_eq_emissions: 0.02238820299105448
---

# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 739422530
- CO2 Emissions (in grams): 0.02238820299105448

## Validation Metrics

- Loss: 0.36623290181159973
- Accuracy: 0.9321753515301903
- Macro F1: 0.9066706944656866
- Micro F1: 0.9321753515301903
- Weighted F1: 0.9314858667247282
- Macro Precision: 0.9489233194839841
- Micro Precision: 0.9321753515301903
- Weighted Precision: 0.9347346558570125
- Macro Recall: 0.8842587178845419
- Micro Recall: 0.9321753515301903
- Weighted Recall: 0.9321753515301903


## 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/ndavid/autotrain-trec-fine-bert-739422530
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("ndavid/autotrain-trec-fine-bert-739422530", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("ndavid/autotrain-trec-fine-bert-739422530", use_auth_token=True)

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

outputs = model(**inputs)
```