Update README.md

README.md

@@ -32,7 +32,14 @@ That is an improvement of almost 12 points over the starcoder 1b baseline, almos
 
 The results (on the human eval benchmark) are on par with other open-source models like StarCoderBase (30.4) StarCoder(33.6) CodeGen-16B-Mono(29.3) while the model being 15 times smaller.
 
-It still underperforms compared to other models like CodeLLama (53%) or chat gpt 4 (82) or wizard coder (73.2), but these model are more than 30 times bigger.
+It still underperforms compared to other models like CodeLLama (53%) chat gpt 4 (82) or wizard coder (73.2), but these model are more than 30 times bigger.
+
+## Finetuning details
+
+We did full parameter fine-tuning and used a Nvidia a40 for 12 hours using a batch size of 128 and a micro-batch size of 8. 
+
+
+To reproduce the training just follow the training instructions in our [open source codebase](https://github.com/jina-ai/textbook)
 
 
 ## Disclaimer
@@ -43,3 +50,6 @@ It still underperforms compared to other models like CodeLLama (53%) or chat gpt
 * This model has not been aligned with human preferences and therefore could potentially generate harmful content
 * This model has been trained on a dataset generated by ChatGPT 3.5, and you should check the legal status of AI-generated content in your jurisdiction before using it. You should make sure that your usage complies with the OpenAI Terms of Use, in so far as legally applicable.
 
+## Credits
+
+This model was trained and released by [Jina.ai](https://jina.ai/)