Update README.md

README.md

@@ -9,14 +9,126 @@ tags:
 license: apache-2.0
 language:
 - en
+pipeline_tag: text-generation
+library_name: transformers
+model-index:
+- name: RA_Reasoner2.0
+  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: 55.92
+      name: strict accuracy
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Daemontatox/RA_Reasoner
+      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: 43.07
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Daemontatox/RA_Reasoner
+      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: 20.09
+      name: exact match
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Daemontatox/RA_Reasoner
+      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: 10.85
+      name: acc_norm
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Daemontatox/RA_Reasoner
+      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: 7.51
+      name: acc_norm
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Daemontatox/RA_Reasoner
+      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: 36.67
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Daemontatox/RA_Reasoner
+      name: Open LLM Leaderboard
 ---
+![RA_REASONER](./image.webp)
+# Uploaded Model
 
-# Uploaded  model
+**Developed by:** Daemontatox
 
-- **Developed by:** Daemontatox
-- **License:** apache-2.0
-- **Finetuned from model :** Daemontatox/RA_Reasoner
+**License:** [Apache 2.0](https://www.apache.org/licenses/LICENSE-2.0)
 
-This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
+**Finetuned from model:** [tiiuae/Falcon3-10B-Instruct](https://huggingface.co/tiiuae/Falcon3-10B-Instruct)
 
-[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
+This model was fine-tuned from the Falcon-10B-Instruct model. It was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Hugging Face's TRL library.
+
+This model is intended for text generation tasks, with a focus on reasoning capabilities and instruction following, similar to capabilities demonstrated by the ChatGPT-O1-Mini model.
+
+## Training Details
+
+This model was fine-tuned with Unsloth and TRL, resulting in significant speed improvements during the training process. Details on specific fine-tuning data, parameters and methods will be added soon. The fine-tuning process has prioritized improving the model's reasoning abilities on various benchmarks.
+
+## Intended Use
+
+This model is intended for research and development purposes related to text generation, instruction following, and complex reasoning tasks. It is suitable for applications that require a model capable of handling multi-step logical problems and understanding nuanced instructions. 
+
+**Focus on Reasoning:** The fine-tuning has been geared towards enhancing the model's ability to tackle reasoning challenges and logic-based tasks.
+
+
+---