update readme

README.md

@@ -16,16 +16,17 @@ pipeline_tag: text-generation
 
 # Swin-DistilBERTimbau
 
-**Swin-DistilBERTimbau** model trained on **Flickr30K Portuguese** (translated version using Google Translator API)
+**Swin-DistilBERTimbau** model trained on [**Flickr30K Portuguese**](https://huggingface.co/datasets/laicsiifes/flickr30k-pt-br) (translated version using Google Translator API)
 at resolution 224x224 and max sequence length of 512 tokens.
 
 
 ## Model Description
 
-The Swin-DistilBERTimbau is a type of Vision Encoder Decoder which leverage the checkpoints of the [Swin Trnasformer](https://huggingface.co/microsoft/swin-base-patch4-window7-224)
+The Swin-DistilBERTimbau is a type of Vision Encoder Decoder which leverage the checkpoints of the [Swin Transformer](https://huggingface.co/microsoft/swin-base-patch4-window7-224)
 as encoder and the checkpoints of the [DistilBERTimbau](https://huggingface.co/adalbertojunior/distilbert-portuguese-cased) as decoder.
 The encoder checkpoints come from Swin Trasnformer version pre-trained on ImageNet-1k at resolution 224x224.
 
+The code used for training and evaluation is available at: https://github.com/laicsiifes/ved-transformer-caption-ptbr.
 
 ## How to Get Started with the Model
 
@@ -53,16 +54,17 @@ generated_text = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)
 print(generated_text)
 ```
 
+## Results
 
-### Results
-
-
+The evaluation metrics Cider-D, BLEU@4, ROUGE-L, METEOR and BERTScore are abbreviated as C, B@4, RL, M and BS, respectively.
 
 |Model|Training|Evaluation|C|B@4|RL|M|BS|
 |-----|--------|----------|-------|------|-------|------|---------|
 |Swin-DistilBERTimbau|Flickr30K Portuguese|Flickr30K Portuguese|66.73|24.65|39.98|44.71|72.30|
 |Swin-GPT-2|Flickr30K Portuguese|Flickr30K Portuguese|64.71|23.15|39.39|44.36|71.70|
 
-**BibTeX:**
+## BibTeX entry and citation info
 
-[More Information Needed]
+```bibtex
+Coming Soon
+```