Update README.md

README.md

@@ -145,35 +145,31 @@ Evaluations on Serbian LLM eval suite (or rather, performance and knowledge of S
 |-----------|-------|-------|-----------|-------|------------|------------|-------|---------|----------|-------|
 | [Zamfir-7B](https://huggingface.co/Stopwolf/Zamfir-7B-slerp) | 51.85 | 32.25 | 46.03     | 75.59 | 62.59      | 26.00      | 66.81 | 16.09   | 36.11    | 45.92 |
 | [Mustra-7B](https://huggingface.co/Stopwolf/Mustra-7B-Instruct-v0.1) | 52.95 | 33.70 | 45.89     | **77.55** | 64.17      | **30.60**      | 67.25 | 15.40   | 34.84    | 46.93 |
-| [Tito-7B](https://huggingface.co/Stopwolf/Tito-7B)   | 55.43 | **34.73** | 48.19     | 77.37 | **65.27**      | 30.00      | 67.30 | **16.7**    | 35.38    | **47.82** |
+| [Tito-7B](https://huggingface.co/Stopwolf/Tito-7B-slerp)   | 55.43 | **34.73** | 48.19     | 77.37 | **65.27**      | 30.00      | 67.30 | **16.7**    | 35.38    | **47.82** |
 | [YugoGPT](https://huggingface.co/gordicaleksa/YugoGPT)   | **57.79** | **34.73** | **49.89**     | 69.45 | 64.56      | 28.20      | **72.03** | 15.82   | **36.14**    | 47.62 |
 
 Here, all benchmarks were done 0-shot, on the exception of NQ Open and TriviaQA which were done in 5-shot manner, in order to be comparable to Mistral paper.
 
+If we try to replicate OpenLLM Leaderboard results on available Serbian datasets (running an appropriate amount of shots instead of 0), we get:
+|         | ARC   | Hellaswag | Winogrande | TruthfulQA | Avg.  |
+|---------|-------|-----------|------------|------------|-------|
+| Tito-7B | 47.27 |     -     |   69.93    |            |   -   |
+| YugoGPT | 44.03 |     -     |   70.64    |            |   -   |
+| [Perucac-7B](https://huggingface.co/Stopwolf/Perucac-7B-slerp)  | 49.74 |   -   | 71.98 | 56.03 |   -   |
+| Llama3-8B | 42.24 |    -    |   61.25    |            |   -   |
 
-Evalutaions on Open LLM Leaderboard (or rather, performance and knowledge of English):
-|         | ARC   | Hellaswag | Winogrande | MMLU | GSM8k | ThruthfulQA | Avg.  |
-|---------|-------|-----------|------------|------|-------|-------------|-------|
-| Tito-7B | 68.08 | 86.37     | 81.69      |64.01 | 63.61 | 57.01       | 70.13 |
-| YugoGPT | 58.10 | 81.44     | 76.56      |60.68 | 30.70 | 36.60       | 57.34 |
 
-Here, Winogrande, GSM8k, MMLU were done in 5-shot manner, Hellaswag in 10-shot manner, and finally ARC in 25-shot manner.
 
-If we try to replicate these approaches on available Serbian datasets (running an appropriate amount of shots instead of 0), we get:
-|         | ARC   | Hellaswag | Winogrande | Avg.  |
-|---------|-------|-----------|------------|-------|
-| Tito-7B | 47.27 |     -     |   69.93    |   -   |
-| YugoGPT | 44.03 |     -     |   70.64    |   -   |
 # [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
 Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_Stopwolf__Tito-7B-slerp)
 
-|             Metric              |Value|
-|---------------------------------|----:|
-|Avg.                             |70.13|
-|AI2 Reasoning Challenge (25-Shot)|68.09|
-|HellaSwag (10-Shot)              |86.38|
-|MMLU (5-Shot)                    |64.01|
-|TruthfulQA (0-shot)              |57.01|
-|Winogrande (5-shot)              |81.69|
-|GSM8k (5-shot)                   |63.61|
+|             Metric              |Tito | YugoGPT |
+|---------------------------------|----:|--------:|
+|Avg.                             |70.13|  57.34  |
+|AI2 Reasoning Challenge (25-Shot)|68.09|  58.10  |
+|HellaSwag (10-Shot)              |86.38|  81.44  |
+|MMLU (5-Shot)                    |64.01|  60.68  |
+|TruthfulQA (0-shot)              |57.01|  36.60  |
+|Winogrande (5-shot)              |81.69|  76.56  |
+|GSM8k (5-shot)                   |63.61|  30.70  |