Adding Evaluation Results (#1)

- Adding Evaluation Results (076212750ff3729ec56f17c9326b0c72506a9919)


Co-authored-by: Open LLM Leaderboard PR Bot <[email protected]>

README.md

@@ -1,14 +1,4 @@
 ---
-license: apache-2.0
-datasets:
-- Epiculous/SynthRP-Gens-v1.1-Filtered-n-Cleaned
-- anthracite-org/stheno-filtered-v1.1
-- PJMixers/hieunguyenminh_roleplay-deduped-ShareGPT
-- Gryphe/Sonnet3.5-Charcard-Roleplay
-- Epiculous/Synthstruct-Gens-v1.1-Filtered-n-Cleaned
-- anthracite-org/kalo-opus-instruct-22k-no-refusal
-- anthracite-org/nopm_claude_writing_fixed
-- anthracite-org/kalo_opus_misc_240827
 language:
 - en
 - fr
@@ -19,7 +9,112 @@ language:
 - ru
 - zh
 - ja
+license: apache-2.0
+datasets:
+- Epiculous/SynthRP-Gens-v1.1-Filtered-n-Cleaned
+- anthracite-org/stheno-filtered-v1.1
+- PJMixers/hieunguyenminh_roleplay-deduped-ShareGPT
+- Gryphe/Sonnet3.5-Charcard-Roleplay
+- Epiculous/Synthstruct-Gens-v1.1-Filtered-n-Cleaned
+- anthracite-org/kalo-opus-instruct-22k-no-refusal
+- anthracite-org/nopm_claude_writing_fixed
+- anthracite-org/kalo_opus_misc_240827
 pipeline_tag: text-generation
+model-index:
+- name: Azure_Dusk-v0.2
+  results:
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: IFEval (0-Shot)
+      type: HuggingFaceH4/ifeval
+      args:
+        num_few_shot: 0
+    metrics:
+    - type: inst_level_strict_acc and prompt_level_strict_acc
+      value: 34.67
+      name: strict accuracy
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Epiculous/Azure_Dusk-v0.2
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: BBH (3-Shot)
+      type: BBH
+      args:
+        num_few_shot: 3
+    metrics:
+    - type: acc_norm
+      value: 17.4
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Epiculous/Azure_Dusk-v0.2
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: MATH Lvl 5 (4-Shot)
+      type: hendrycks/competition_math
+      args:
+        num_few_shot: 4
+    metrics:
+    - type: exact_match
+      value: 1.66
+      name: exact match
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Epiculous/Azure_Dusk-v0.2
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: GPQA (0-shot)
+      type: Idavidrein/gpqa
+      args:
+        num_few_shot: 0
+    metrics:
+    - type: acc_norm
+      value: 1.45
+      name: acc_norm
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Epiculous/Azure_Dusk-v0.2
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: MuSR (0-shot)
+      type: TAUR-Lab/MuSR
+      args:
+        num_few_shot: 0
+    metrics:
+    - type: acc_norm
+      value: 6.37
+      name: acc_norm
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Epiculous/Azure_Dusk-v0.2
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: MMLU-PRO (5-shot)
+      type: TIGER-Lab/MMLU-Pro
+      config: main
+      split: test
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 22.6
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Epiculous/Azure_Dusk-v0.2
+      name: Open LLM Leaderboard
 ---
 
 ![image/png](https://cdn-uploads.huggingface.co/production/uploads/64adfd277b5ff762771e4571/NGEOrcWYPDnFmvHinkXVk.png)
@@ -52,4 +147,17 @@ The v0.2 models are trained on ChatML, please use that Context and Instruct temp
 ## Training
 Training was done twice over 2 epochs each on two 2x [NVIDIA A6000 GPUs](https://www.nvidia.com/en-us/design-visualization/rtx-a6000/) using LoRA. A two-phased approach was used in which the base model was trained 2 epochs on RP data, the LoRA was then applied to base. Finally, the new modified base was trained 2 epochs on instruct, and the new instruct LoRA was applied to the modified base, resulting in what you see here.
 
-[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
+[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
+# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
+Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_Epiculous__Azure_Dusk-v0.2)
+
+|      Metric       |Value|
+|-------------------|----:|
+|Avg.               |14.03|
+|IFEval (0-Shot)    |34.67|
+|BBH (3-Shot)       |17.40|
+|MATH Lvl 5 (4-Shot)| 1.66|
+|GPQA (0-shot)      | 1.45|
+|MuSR (0-shot)      | 6.37|
+|MMLU-PRO (5-shot)  |22.60|
+