Adding Evaluation Results

README.md

@@ -1,10 +1,6 @@
 ---
-license_name: tongyi-qianwen-research
-license_link: https://huggingface.co/Qwen/Qwen1.5-1.8B-Chat/raw/main/LICENSE
-library_name: transformers
 license: other
-datasets:
-- teknium/OpenHermes-2.5
+library_name: transformers
 tags:
 - chatml
 - finetune
@@ -12,6 +8,113 @@ tags:
 - synthetic data
 - custom_code
 - qwen2
+datasets:
+- teknium/OpenHermes-2.5
+license_name: tongyi-qianwen-research
+license_link: https://huggingface.co/Qwen/Qwen1.5-1.8B-Chat/raw/main/LICENSE
+model-index:
+- name: Reyna-Mini-1.8B-v0.1
+  results:
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: AI2 Reasoning Challenge (25-Shot)
+      type: ai2_arc
+      config: ARC-Challenge
+      split: test
+      args:
+        num_few_shot: 25
+    metrics:
+    - type: acc_norm
+      value: 35.24
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=aloobun/Reyna-Mini-1.8B-v0.1
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: HellaSwag (10-Shot)
+      type: hellaswag
+      split: validation
+      args:
+        num_few_shot: 10
+    metrics:
+    - type: acc_norm
+      value: 60.42
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=aloobun/Reyna-Mini-1.8B-v0.1
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: MMLU (5-Shot)
+      type: cais/mmlu
+      config: all
+      split: test
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 45.37
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=aloobun/Reyna-Mini-1.8B-v0.1
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: TruthfulQA (0-shot)
+      type: truthful_qa
+      config: multiple_choice
+      split: validation
+      args:
+        num_few_shot: 0
+    metrics:
+    - type: mc2
+      value: 41.4
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=aloobun/Reyna-Mini-1.8B-v0.1
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: Winogrande (5-shot)
+      type: winogrande
+      config: winogrande_xl
+      split: validation
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 60.85
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=aloobun/Reyna-Mini-1.8B-v0.1
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: GSM8k (5-shot)
+      type: gsm8k
+      config: main
+      split: test
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 5.46
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=aloobun/Reyna-Mini-1.8B-v0.1
+      name: Open LLM Leaderboard
 ---
 
 ![Reyna aloobun qwen0.5B](https://i.imgur.com/QfbOY6c.jpeg)
@@ -94,4 +197,17 @@ op = model.generate(
 ## Output:
 > One real-world scenario where understanding probability theory can make a significant difference in decision-making is in the field of finance. Financial institutions, such as banks and investment firms, must make decisions about lending money to individuals or businesses, and how much risk they should take on.
 > In this case, understanding probability theory would help financial analysts and investors make more informed decisions by providing them with information about the likelihood of different outcomes. For example, if an investor wants to invest in a particular stock, they might want to understand the probability that it will perform well over time, based on historical data and market trends. They might also be interested in understanding the probability of defaulting on a loan, which would help them evaluate whether it's worth taking on that risk.
-> Probability theory provides valuable insights into how events are likely to occur and what factors contribute to those probabilities. By using statistical models and simulations, financial professionals can estimate the likelihood of different scenarios and make better-informed decisions about how to allocate their resources. This can lead to increased profits for financial institutions and improved customer satisfaction for individual investors.<|im_end|>
+> Probability theory provides valuable insights into how events are likely to occur and what factors contribute to those probabilities. By using statistical models and simulations, financial professionals can estimate the likelihood of different scenarios and make better-informed decisions about how to allocate their resources. This can lead to increased profits for financial institutions and improved customer satisfaction for individual investors.<|im_end|>
+# [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_aloobun__Reyna-Mini-1.8B-v0.1)
+
+|             Metric              |Value|
+|---------------------------------|----:|
+|Avg.                             |41.46|
+|AI2 Reasoning Challenge (25-Shot)|35.24|
+|HellaSwag (10-Shot)              |60.42|
+|MMLU (5-Shot)                    |45.37|
+|TruthfulQA (0-shot)              |41.40|
+|Winogrande (5-shot)              |60.85|
+|GSM8k (5-shot)                   | 5.46|
+