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News-Categorizer
rahul004/News-Categorizer
News-Categorizer is a text classification model from rahul004. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.
- Developed by: Rahul A Gowda - Model type: Encoder Based Model - License: apache-2.0 - Finetuned from model [optional]: Distledbert-base-uncased
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- distilbert
- Access
- Public
- Created
- Aug 10, 2024
- Updated
- Aug 10, 2024
- SHA
- 6fcc8856
Try a prompt
Model card
From the Hugging Face model README
Model Description
- Developed by: Rahul A Gowda
- Model type: Encoder Based Model
- License: apache-2.0
- Finetuned from model [optional]: Distledbert-base-uncased
Model Sources [optional]
<!-- Provide the basic links for the model. -->How to Get Started with the Model
Use the code below to get started with the model.
Training Data
The Model has been fine-tuned on "AG-news" dataset
Evaluation
Total number of epochs: 4
Training Loss: 0.124300
Validation Loss: 0.920658
Accuracy: 0.920658
F1: 0.92054
Use a pipeline as a high-level helper or Load model directly
from transformers import pipeline
pipe = pipeline("text-classification", model="rahul004/News-Categorizer")
---------------x-----------x------------x-------------x------------------
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("rahul004/News-Categorizer")
model = AutoModelForSequenceClassification.from_pretrained("rahul004/News-Categorizer")
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Languages
- en
- Created
- Aug 10, 2024
- Updated
- Aug 10, 2024