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--- |
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language: |
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- en |
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license: apache-2.0 |
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tags: |
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- openllama |
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- 3b |
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datasets: |
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- totally-not-an-llm/EverythingLM-data-V3 |
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model-index: |
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- name: open-llama-3b-v2-elmv3 |
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results: |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: AI2 Reasoning Challenge (25-Shot) |
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type: ai2_arc |
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config: ARC-Challenge |
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split: test |
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args: |
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num_few_shot: 25 |
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metrics: |
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- type: acc_norm |
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value: 42.06 |
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name: normalized accuracy |
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source: |
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url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=aloobun/open-llama-3b-v2-elmv3 |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: HellaSwag (10-Shot) |
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type: hellaswag |
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split: validation |
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args: |
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num_few_shot: 10 |
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metrics: |
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- type: acc_norm |
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value: 73.28 |
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name: normalized accuracy |
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source: |
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url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=aloobun/open-llama-3b-v2-elmv3 |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: MMLU (5-Shot) |
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type: cais/mmlu |
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config: all |
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split: test |
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args: |
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num_few_shot: 5 |
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metrics: |
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- type: acc |
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value: 27.61 |
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name: accuracy |
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source: |
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url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=aloobun/open-llama-3b-v2-elmv3 |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: TruthfulQA (0-shot) |
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type: truthful_qa |
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config: multiple_choice |
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split: validation |
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args: |
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num_few_shot: 0 |
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metrics: |
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- type: mc2 |
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value: 35.54 |
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source: |
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url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=aloobun/open-llama-3b-v2-elmv3 |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: Winogrande (5-shot) |
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type: winogrande |
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config: winogrande_xl |
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split: validation |
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args: |
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num_few_shot: 5 |
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metrics: |
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- type: acc |
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value: 64.96 |
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name: accuracy |
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source: |
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url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=aloobun/open-llama-3b-v2-elmv3 |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: GSM8k (5-shot) |
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type: gsm8k |
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config: main |
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split: test |
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args: |
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num_few_shot: 5 |
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metrics: |
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- type: acc |
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value: 3.41 |
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name: accuracy |
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source: |
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url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=aloobun/open-llama-3b-v2-elmv3 |
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name: Open LLM Leaderboard |
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--- |
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Trained on 3 epoch of the EverythingLM data. |
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Eval Results : |
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![image/png](https://huggingface.co./aloobun/open-llama-3b-v2-elmv3/resolve/main/assets/lm-eval.png) |
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I like to tweak smaller models than 3B and mix loras, but now I'm trying my hand at finetuning a 3B model. Lets see how it goes. |
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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard) |
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Detailed results can be found [here](https://huggingface.co./datasets/open-llm-leaderboard/details_aloobun__open-llama-3b-v2-elmv3) |
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| Metric |Value| |
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|---------------------------------|----:| |
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|Avg. |41.14| |
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|AI2 Reasoning Challenge (25-Shot)|42.06| |
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|HellaSwag (10-Shot) |73.28| |
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|MMLU (5-Shot) |27.61| |
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|TruthfulQA (0-shot) |35.54| |
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|Winogrande (5-shot) |64.96| |
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|GSM8k (5-shot) | 3.41| |
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