added benchmark info

README.md

@@ -63,10 +63,6 @@ dataset_info:
 MüşteriYorumları is a Turkish e-commerce customer reviews dataset of size 103K, scraped from Hepsiburada.com and Trendyol.com. These reviews encompass a wide
 array of product categories, including apparel, food items, baby products, and books. Review stars are in range of 1-5 stars.
 
-
-This dataset is a part of [SentiTurca](https://huggingface.co/datasets/turkish-nlp-suite/SentiTurca) benchmark, in the benchmark the subset name is **e-commerce**, named according to the GLUE tasks.
-Model benchmarking information can be found under SentiTurca HF repo and benchmarking scripts can be found under [SentiTurca Github repo](https://github.com/turkish-nlp-suite/SentiTurca).
-
 The star distribution is as follows:
 
 
@@ -79,7 +75,7 @@ The star distribution is as follows:
 | 5  | 30,314 |
 | total | 103,920 |
 
-The star distribution is quite skewed towards 4+ reviews.
+The star distribution is quite skewed towards 4+ reviews. For more information about dataset statistics, please refer to the [research paper]().
 
 ## Dataset Instances
 
@@ -92,13 +88,29 @@ An instance looks like:
 }
 ```
 
-
-
 ## Data Split
 
 |  name   |train|validation|test|
 |---------|----:|---:|---:|
 |MüşteriYorumları Customer Reviews|73920|15000|15000|
 
+
+## Benchmarking
+This dataset is a part of [SentiTurca](https://huggingface.co/datasets/turkish-nlp-suite/SentiTurca) benchmark, in the benchmark the subset name is **e-commerce**, named according to the GLUE tasks.
+Model benchmarking information can be found under SentiTurca HF repo and benchmarking scripts can be found under [SentiTurca Github repo](https://github.com/turkish-nlp-suite/SentiTurca).
+
+For this dataset we benchmarked a transformer based model BERTurk and a handful of LLMs. Success of each model is follows:
+
+| Model | acc./F1 |
+|---|---|
+| Gemini 1.0 Pro  | 1.0/1.0 |
+| GPT-4 Turbo  | 0.64/0.63 |
+| Claude 3 Sonnet  | 0.57/0.53 |
+| Llama 3 70B | 0.58/0.55 |
+| Qwen2-72B  | 0.53/0.50 |
+| BERTurk | 0.66/0.64 |
+
+For a critique of the results, misclassified instances and more please consult to the [research paper]().
+
 ## Citation
 Coming soon!!