Update README.md

README.md

@@ -20,8 +20,11 @@ This is a Huggingface model fine-tuned on the CNN news dataset for zero-shot tex
 ## Authors
 This work was done by [CHERGUELAINE Ayoub](https://www.linkedin.com/in/ayoub-cherguelaine/) & [BOUBEKRI Faycal](https://www.linkedin.com/in/faycal-boubekri-832848199/)
 
+## Original Model
+[facebook/bart-large-mnli](https://huggingface.co/facebook/bart-large-mnli)
+
 ## Model Architecture
-The model architecture is based on the BART-MNLI transformer model. BART (Bidirectional and Auto-Regressive Transformers) is a denoising autoencoder that is pre-trained on a large corpus of text and fine-tuned on downstream natural language processing tasks.
+The BART-Large-MNLI model has 12 transformer layers, a hidden size of 1024, and 406 million parameters. It is pre-trained on the English Wikipedia and BookCorpus datasets, and fine-tuned on the Multi-Genre Natural Language Inference (MNLI) task.
 
 ## Dataset
 The CNN news dataset was used for fine-tuning the model. This dataset contains news articles from the CNN website and is labeled into 6 categories, including politics, health, entertainment, tech, travel, world, and sports.