Update README.md

README.md

@@ -29,11 +29,17 @@ configs:
     path: data/validation-*
 ---
 
-Experiments on training Auto Regressive models for text-to-image generation
+## Experiments for training Auto Regressive models for text-to-image generation
 
-This dataset is derived from [conceptual captions](https://huggingface.co/datasets/google-research-datasets/conceptual_captions) (CC3M) which contains roughly 3.3M image and caption pairs
-For images we use [1d-tokenizer](https://github.com/bytedance/1d-tokenizer) by bytedance which tokenizes a 256 * 256 image into 32 tokens while still achieving SOTA fidelity ratio
-For text we train a BPE based tokenized on the captions. For training we use the standard cross entropy loss between the logits and the targets
+This dataset is derived from [conceptual captions](https://huggingface.co/datasets/pixparse/cc3m-wds) (CC3M) which contains roughly 3.3M image and caption pairs
+
+For images we use [1d-tokenizer](https://github.com/bytedance/1d-tokenizer) by [bytedance](https://www.bytedance.com/en/) which tokenizes a 256 * 256 image into 32 tokens while still achieving SOTA fidelity ratio
+
+For text we train a BPE based tokenizer on the image captions dataset with a vocab size set to 30K, where 4096 tokens where used to represent images, 9 to represent some special tokens and the remaining 25895 tokens for text
+
+## Training Procedure
+
+For training we prompt the model to generate an image based on a text such as: ""
 
 | Train Iter | hard rock artist performing music | football player during a match | concept vector illustration showing a flag | police officer and soldiers arrest military combatant | bird on a tree |
 | ---- | ---- | ---- | ---- | ---- | ---- |