55 lines
1.7 KiB
Markdown
55 lines
1.7 KiB
Markdown
---
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library_name: transformers
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license: llama2
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datasets:
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- aqua_rat
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- microsoft/orca-math-word-problems-200k
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- m-a-p/CodeFeedback-Filtered-Instruction
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- anon8231489123/ShareGPT_Vicuna_unfiltered
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---
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# Llama-3-Smaug-8B
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### Built with Meta Llama 3
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This model was built using the Smaug recipe for improving performance on real world multi-turn conversations applied to
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[meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct).
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### Model Description
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- **Developed by:** [Abacus.AI](https://abacus.ai)
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- **License:** https://llama.meta.com/llama3/license/
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- **Finetuned from model:** [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct).
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## Evaluation
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### MT-Bench
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```
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########## First turn ##########
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score
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model turn
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Llama-3-Smaug-8B 1 8.77500
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Meta-Llama-3-8B-Instruct 1 8.31250
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########## Second turn ##########
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score
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model turn
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Meta-Llama-3-8B-Instruct 2 7.8875
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Llama-3-Smaug-8B 2 7.8875
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########## Average ##########
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score
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model
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Llama-3-Smaug-8B 8.331250
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Meta-Llama-3-8B-Instruct 8.10
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```
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| Model | First turn | Second Turn | Average |
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| :---- | ---------: | ----------: | ------: |
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| Llama-3-Smaug-8B | 8.78 | 7.89 | 8.33 |
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| Llama-3-8B-Instruct | 8.31 | 7.89 | 8.10 |
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This version of Smaug uses new techniques and new data compared to [Smaug-72B](https://huggingface.co/abacusai/Smaug-72B-v0.1), and more information will be released later on. For now, see the previous Smaug paper: https://arxiv.org/abs/2402.13228. |