|
|
--- |
|
|
tags: autotrain |
|
|
language: unk |
|
|
widget: |
|
|
- text: "I love AutoTrain 🤗" |
|
|
datasets: |
|
|
- deepesh0x/autotrain-data-bert_wikipedia_sst2 |
|
|
co2_eq_emissions: 16.368556687663705 |
|
|
--- |
|
|
|
|
|
# Model Trained Using AutoTrain |
|
|
|
|
|
- Problem type: Binary Classification |
|
|
- Model ID: 1021934687 |
|
|
- CO2 Emissions (in grams): 16.368556687663705 |
|
|
|
|
|
## Validation Metrics |
|
|
|
|
|
- Loss: 0.15712647140026093 |
|
|
- Accuracy: 0.9503340757238308 |
|
|
- Precision: 0.9515767251616308 |
|
|
- Recall: 0.9598083577322332 |
|
|
- AUC: 0.9857179850355002 |
|
|
- F1: 0.9556748161399324 |
|
|
|
|
|
## 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/deepesh0x/autotrain-bert_wikipedia_sst2-1021934687 |
|
|
``` |
|
|
|
|
|
Or Python API: |
|
|
|
|
|
``` |
|
|
from transformers import AutoModelForSequenceClassification, AutoTokenizer |
|
|
|
|
|
model = AutoModelForSequenceClassification.from_pretrained("deepesh0x/autotrain-bert_wikipedia_sst2-1021934687", use_auth_token=True) |
|
|
|
|
|
tokenizer = AutoTokenizer.from_pretrained("deepesh0x/autotrain-bert_wikipedia_sst2-1021934687", use_auth_token=True) |
|
|
|
|
|
inputs = tokenizer("I love AutoTrain", return_tensors="pt") |
|
|
|
|
|
outputs = model(**inputs) |
|
|
``` |
