bert2 / README.md
madmancity's picture
Update README.md
e40fcb4
---
tags:
- autotrain
- text-classification
language:
- en
widget:
- text: "What is your opinion on cheese?"
datasets:
- madmancity/autotrain-data-bert1
co2_eq_emissions:
emissions: 0.30639014520838476
---
- Problem type: Multi-class Classification
- Model ID: 45066113192
- CO2 Emissions (in grams): 0.3064
## Validation Metrics
- Loss: 0.527
- Accuracy: 0.825
- Macro F1: 0.815
- Micro F1: 0.825
- Weighted F1: 0.816
- Macro Precision: 0.844
- Micro Precision: 0.825
- Weighted Precision: 0.843
- Macro Recall: 0.823
- Micro Recall: 0.825
- Weighted Recall: 0.825
## 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/madmancity/autotrain-bert1-45066113192
```
Or Python API:
```
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("madmancity/autotrain-bert1-45066113192", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("madmancity/autotrain-bert1-45066113192", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt")
outputs = model(**inputs)
```