---
tags:
- autotrain
- text-classification
language:
- en
widget:
- text: "I love AutoTrain"
datasets:
- MarketingHHM/autotrain-data-predictiveoutcomestranscripts
co2_eq_emissions:
  emissions: 1.844844508241562
---

# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 65459136117
- CO2 Emissions (in grams): 1.8448

## Validation Metrics

- Loss: 1.543
- Accuracy: 0.409
- Macro F1: 0.218
- Micro F1: 0.409
- Weighted F1: 0.340
- Macro Precision: 0.194
- Micro Precision: 0.409
- Weighted Precision: 0.299
- Macro Recall: 0.260
- Micro Recall: 0.409
- Weighted Recall: 0.409


## 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/MarketingHHM/autotrain-predictiveoutcomestranscripts-65459136117
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("MarketingHHM/autotrain-predictiveoutcomestranscripts-65459136117", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("MarketingHHM/autotrain-predictiveoutcomestranscripts-65459136117", use_auth_token=True)

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

outputs = model(**inputs)
```