Added a simple definition of CLIP-Italian as Introduction

introduction.md

@@ -1,6 +1,6 @@
 # CLIP-Italian
 
-CLIP ([Radford et al., 2021](https://arxiv.org/abs/2103.00020)) is an amazing model that can learn to represent images and text jointly in the same space.
+CLIP-Italian is a multimodal model trained on ~1.4 million Italian text-image pairs using Italian Bert model as text encoder and Vision Transformer(ViT) as image encoder.Clip-Italian (Contrastive Language-Image Pre-training in Italian language) is based on OpenAI’s CLIP ([Radford et al., 2021](https://arxiv.org/abs/2103.00020))which is an amazing model that can learn to represent images and text jointly in the same space.
 
 In this project, we aim to propose the first CLIP model trained on Italian data, that in this context can be considered a
 low resource language. Using a few techniques, we have been able to fine-tune a SOTA Italian CLIP model with **only 1.4 million** training samples. Our Italian CLIP model
@@ -173,7 +173,7 @@ We selected two different tasks:
 + zero-shot classification, in which given an image and a set of captions (or labels), the model finds 
 the best matching caption for the image 
 
-### Reproducibiliy
+### Reproducibility
 
 In order to make both experiments very easy to replicate, we share the colab notebooks we used to compute the results.