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--- |
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license: apache-2.0 |
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language: |
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- en |
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datasets: |
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- appvoid/no-prompt-15k |
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pipeline_tag: text-generation |
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--- |
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![palmer](https://huggingface.co/appvoid/no-prompt-1.3b/resolve/main/_ccd1a5dd-2ddc-4d5a-8163-fd6d1b39f5f4.jpeg?download=true) |
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# no-prompt |
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### a sheared-llama-1.3b fine-tuning |
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This model uses an 1.3 billion parameters model as base to be further fine-tuned on the same data as palmer. It works pretty good and even surpasses sota model on `hellaswag`. |
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### evaluation |
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|Model| ARC_C| HellaSwag| PIQA| Winogrande| |
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|------|-----|-----------|------|-------------| |
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|tinyllama-2t| 0.2807| 0.5463| 0.7067| 0.5683| |
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|palmer-001 | 0.2807| 0.5524| 0.7106| 0.5896| |
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|sheared-1.3b| 0.2910| 0.5935| 0.7339| 0.5809| |
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|no-prompt-1.3b| 0.3157| **0.6022**| 0.7334| 0.5864| |
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|falcon-rw-1b-instruct-openorca (sota) | **0.3362**| 0.5997| **0.7394**| **0.6148**| |
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This model was trained on less than 25% of the dataset yet achieves competitive performance to current sota on open llm leaderboard. |
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### training |
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Training took ~5 P100 gpu hours. It was trained on 15,000 gpt-4 shuffled samples. palmer was fine-tuned using lower learning rates ensuring it keeps as much general knowledge as possible. |
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### prompt |
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``` |
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no prompt |
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``` |
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### limitations |
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Hallucinations are frequent, just as any transformer model this size. |
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