Update README.md

README.md

@@ -2,18 +2,19 @@
 tags:
 - summarization
 widget:
-- text: "public static < T , U > Function < T , U > castFunction  ( Class < U > target ) { return new CastToClass < T , U > ( target ) ; }"
+- text: "protected String renderUri ( URI uri ) { return uri . toASCIIString ( ) ; }"
 
 ---
 
-# CodeTrans model for code documentation generation java
+
+# CodeTrans model for code comment generation java
 Pretrained model on programming language java using the t5 small model architecture. It was first released in
 [this repository](https://github.com/agemagician/CodeTrans). This model is trained on tokenized java code functions: it works best with tokenized java functions.
 
 
 ## Model description
 
-This CodeTrans model is based on the `t5-small` model. It has its own SentencePiece vocabulary model. It used multi-task training on 13 supervised tasks in the software development domain and 7 unsupervised datasets. It is then fine-tuned on the code documentation generation task for the java function/method.
+This CodeTrans model is based on the `t5-small` model. It has its own SentencePiece vocabulary model. It used multi-task training on 13 supervised tasks in the software development domain and 7 unsupervised datasets. It is then fine-tuned on the code comment generation task for the java function/method.
 
 ## Intended uses & limitations
 
@@ -27,30 +28,31 @@ Here is how to use this model to generate java function documentation using Tran
 from transformers import AutoTokenizer, AutoModelWithLMHead, SummarizationPipeline
 
 pipeline = SummarizationPipeline(
-    model=AutoModelWithLMHead.from_pretrained("SEBIS/code_trans_t5_small_code_documentation_generation_java_multitask_finetune"),
-    tokenizer=AutoTokenizer.from_pretrained("SEBIS/code_trans_t5_small_code_documentation_generation_java_multitask_finetune", skip_special_tokens=True),
+    model=AutoModelWithLMHead.from_pretrained("SEBIS/code_trans_t5_small_code_comment_generation_java_multitask_finetune"),
+    tokenizer=AutoTokenizer.from_pretrained("SEBIS/code_trans_t5_small_code_comment_generation_java_multitask_finetune", skip_special_tokens=True),
     device=0
 )
 
-tokenized_code = "public static < T , U > Function < T , U > castFunction  ( Class < U > target ) { return new CastToClass < T , U > ( target ) ; }"
+tokenized_code = "protected String renderUri ( URI uri ) { return uri . toASCIIString ( ) ; }"
 pipeline([tokenized_code])
 ```
-Run this example in [colab notebook](https://github.com/agemagician/CodeTrans/blob/main/prediction/multitask/fine-tuning/function%20documentation%20generation/java/small_model.ipynb).
+Run this example in [colab notebook](https://github.com/agemagician/CodeTrans/blob/main/prediction/multitask/fine-tuning/code%20comment%20generation/small_model.ipynb).
 ## Training data
 
 The supervised training tasks datasets can be downloaded on [Link](https://www.dropbox.com/sh/488bq2of10r4wvw/AACs5CGIQuwtsD7j_Ls_JAORa/finetuning_dataset?dl=0&subfolder_nav_tracking=1)
 
+
 ## Training procedure
 
 ### Multi-task Pretraining
 
-The model was trained on a single TPU Pod V3-8 for half million steps in total, using sequence length 512 (batch size 4096).
+The model was trained on a single TPU Pod V3-8 for 260,000 steps in total, using sequence length 512 (batch size 4096).
 It has a total of approximately 220M parameters and was trained using the encoder-decoder architecture.
 The optimizer used is AdaFactor with inverse square root learning rate schedule for pre-training.
 
 ### Fine-tuning
 
-This model was then fine-tuned on a single TPU Pod V2-8 for 4000 steps in total, using sequence length 512 (batch size 256), using only the dataset only containing java code.
+This model was then fine-tuned on a single TPU Pod V2-8 for 750,000 steps in total, using sequence length 512 (batch size 256), using only the dataset only containing java code.
 
 
 ## Evaluation results
@@ -59,20 +61,23 @@ For the code documentation tasks, different models achieves the following result
 
 Test results :
 
-|   Language / Model   |     Python     |      Java      |       Go       |      Php       |      Ruby      |   JavaScript   |
-| -------------------- | :------------: | :------------: | :------------: | :------------: | :------------: | :------------: |
-|   CodeTrans-ST-Small    |      17.31     |     16.65      |     16.89      |     23.05      |      9.19      |      13.7      |
-|   CodeTrans-ST-Base     |      16.86     |     17.17      |     17.16      |     22.98      |      8.23      |      13.17     |   
-|   CodeTrans-TF-Small    |      19.93     |     19.48      |     18.88      |     25.35      |     13.15      |      17.23     |
-|   CodeTrans-TF-Base     |      20.26     |     20.19      |     19.50      |     25.84      |     14.07      |      18.25     |
-|   CodeTrans-TF-Large    |      20.35     |     20.06      |   **19.54**    |     26.18      |     14.94      |    **18.98**   |
-|   CodeTrans-MT-Small    |      19.64     |     19.00      |     19.15      |     24.68      |     14.91      |      15.26     |
-|   CodeTrans-MT-Base     |    **20.39**   |     21.22      |     19.43      |   **26.23**    |   **15.26**    |      16.11     |
-|   CodeTrans-MT-Large    |      20.18     |   **21.87**    |     19.38      |     26.08      |     15.00      |      16.23     |
-|   CodeTrans-MT-TF-Small |      19.77     |     20.04      |     19.36      |     25.55      |     13.70      |      17.24     |
-|   CodeTrans-MT-TF-Base  |      19.77     |     21.12      |     18.86      |     25.79      |     14.24      |      18.62     |
-|   CodeTrans-MT-TF-Large |      18.94     |     21.42      |     18.77      |     26.20      |     14.19      |      18.83     |
-|   State of the art   |      19.06     |     17.65      |     18.07      |     25.16      |     12.16      |      14.90     |
+|   Language / Model   |      Java      |
+| -------------------- | :------------: |
+|   CodeTrans-ST-Small    |     37.98      |
+|   CodeTrans-ST-Base     |     38.07      |
+|   CodeTrans-TF-Small    |     38.56      |
+|   CodeTrans-TF-Base     |     39.06      |
+|   CodeTrans-TF-Large    |   **39.50**    |
+|   CodeTrans-MT-Small    |     20.15      |
+|   CodeTrans-MT-Base     |     27.44      |
+|   CodeTrans-MT-Large    |     34.69      |
+|   CodeTrans-MT-TF-Small |     38.37      |
+|   CodeTrans-MT-TF-Base  |     38.90      |
+|   CodeTrans-MT-TF-Large |     39.25      |
+|   State of the art   |     38.17      |
+
 
 
 > Created by [Ahmed Elnaggar](https://twitter.com/Elnaggar_AI) | [LinkedIn](https://www.linkedin.com/in/prof-ahmed-elnaggar/) and Wei Ding | [LinkedIn](https://www.linkedin.com/in/wei-ding-92561270/)
+
+