neg pos
---
tags: autotrain
language: en
widget:
- text: "I love AutoTrain 🤗"
datasets:
- ameerazam08/autotrain-data-imdb
co2_eq_emissions: 0.07308302140406821
---

# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 1166543171
- CO2 Emissions (in grams): 0.07308302140406821

## Validation Metrics

- Loss: 0.2211569994688034
- Accuracy: 0.9138
- Precision: 0.9020598523124758
- Recall: 0.9284
- AUC: 0.9711116000000001
- F1: 0.9150404100137985

## 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/ameerazam08/autotrain-imdb-1166543171
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("ameerazam08/autotrain-imdb-1166543171", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("ameerazam08/autotrain-imdb-1166543171", use_auth_token=True)

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

outputs = model(**inputs)
```