Update README.md

README.md

@@ -42,7 +42,7 @@ print(tokenizer.decode(outputs[0]))
 ### Training Data  
 The base model is pre-trained on [vngrs-web-corpus](https://huggingface.co/datasets/vngrs-ai/vngrs-web-corpus). It is curated by cleaning and filtering Turkish parts of [OSCAR-2201](https://huggingface.co/datasets/oscar-corpus/OSCAR-2201) and [mC4](https://huggingface.co/datasets/mc4) datasets. These datasets consist of documents of unstructured web crawl data. More information about the dataset can be found on their respective pages. Data is filtered using a set of heuristics and certain rules, explained in the appendix of our [paper](https://arxiv.org/abs/2403.01308).
 
-The fine-tuning dataset is a mixture of [OpenSubtitles](https://huggingface.co/datasets/open_subtitles), [TED Talks (2013)](https://wit3.fbk.eu/home) and [Tatoeba](https://tatoeba.org/en/) datasets.
+The fine-tuning dataset is the Turkish sections of [MLSum](https://huggingface.co/datasets/mlsum), [TRNews](https://huggingface.co/datasets/batubayk/TR-News), [XLSum](https://huggingface.co/datasets/csebuetnlp/xlsum) and [Wikilingua](https://huggingface.co/datasets/wiki_lingua) datasets.
 
 ### Limitations
 This model is fine-tuned for paraphrasing tasks. It is not intended to be used in any other case and can not be fine-tuned to any other task with full performance of the base model. It is also not guaranteed that this model will work without specified prompts.
@@ -68,11 +68,11 @@ Pre-trained for 30 days and for a total of 708B tokens. Finetuned for 20 epoch.
 - **Optimizer** : Adam optimizer (β1 = 0.9, β2 = 0.98, Ɛ = 1e-6)
 - **Scheduler**: Linear decay scheduler
 - **Dropout**: 0.1 
--  **Learning rate**: 5e-5
+-  **Learning rate**: 1e-5
 -  **Fine-tune epochs**: 20
 
 #### Metrics
-![image/png](https://cdn-uploads.huggingface.co/production/uploads/62f8b3c84588fe31f435a92b/l8PaGu_OUwWKjHQDIP_X4.png)
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/62f8b3c84588fe31f435a92b/nrM_FA3bGk9NAYW_044HW.png)
 
 ## Citation  
 ```