---
tags:
- autotrain
- text-classification
language:
- unk
widget:
- text: "I love AutoTrain 🤗"
datasets:
- jfan-98/autotrain-data-LegalLong_on_contracts
co2_eq_emissions:
  emissions: 47.64808387548789
---

# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 1230246837
- CO2 Emissions (in grams): 47.6481

## Validation Metrics

- Loss: 0.265
- Accuracy: 0.943
- Macro F1: 0.944
- Micro F1: 0.943
- Weighted F1: 0.943
- Macro Precision: 0.947
- Micro Precision: 0.943
- Weighted Precision: 0.944
- Macro Recall: 0.943
- Micro Recall: 0.943
- Weighted Recall: 0.943

# - Macro F1: 0.944
# - Micro F1: 0.943
# - Macro Precision: 0.947
# - Micro Precision: 0.943
# - Macro Recall: 0.943
# - Micro Recall: 0.943



## 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/jfan-98/autotrain-LegalLong_on_contracts-1230246837
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("jfan-98/autotrain-LegalLong_on_contracts-1230246837", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("jfan-98/autotrain-LegalLong_on_contracts-1230246837", use_auth_token=True)

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

outputs = model(**inputs)
```