Update README.md

README.md

@@ -25,12 +25,12 @@ model-index:
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 should probably proofread and complete it, then remove this comment. -->
 
-# vqa
+# Graphcore/lxmert-vqa-uncased
+
+Optimum Graphcore is a new open-source library and toolkit that enables developers to access IPU-optimized models certified by Hugging Face. It is an extension of Transformers, providing a set of performance optimization tools enabling maximum efficiency to train and run models on Graphcore’s IPUs - a completely new kind of massively parallel processor to accelerate machine intelligence. Learn more about how to take train Transformer models faster with IPUs at [hf.co/hardware/graphcore](https://huggingface.co/hardware/graphcore).
+
+Through HuggingFace Optimum, Graphcore released ready-to-use IPU-trained model checkpoints and IPU configuration files to make it easy to train models with maximum efficiency in the IPU. Optimum shortens the development lifecycle of your AI models by letting you plug-and-play any public dataset and allows a seamless integration to our State-of-the-art hardware giving you a quicker time-to-value for your AI project.
 
-This model is a fine-tuned version of [unc-nlp/lxmert-base-uncased](https://huggingface.co/unc-nlp/lxmert-base-uncased) on the [Graphcore/vqa-lxmert](https://huggingface.co/datasets/Graphcore/vqa-lxmert) dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.0009
-- Accuracy: 0.7242
 
 ## Model description
 
@@ -40,11 +40,14 @@ Paper link : [LXMERT: Learning Cross-Modality Encoder Representations from Trans
 
 ## Intended uses & limitations
 
-More information needed
+This model is a fine-tuned version of [unc-nlp/lxmert-base-uncased](https://huggingface.co/unc-nlp/lxmert-base-uncased) on the [Graphcore/vqa-lxmert](https://huggingface.co/datasets/Graphcore/vqa-lxmert) dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0009
+- Accuracy: 0.7242
 
 ## Training and evaluation data
 
-[Graphcore/vqa-lxmert](https://huggingface.co/datasets/Graphcore/vqa-lxmert) dataset
+- [Graphcore/vqa-lxmert](https://huggingface.co/datasets/Graphcore/vqa-lxmert) dataset
 
 ## Training procedure