32 lines
1.2 KiB
Markdown
32 lines
1.2 KiB
Markdown
---
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base_model: Mihaiii/Pallas-0.5
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inference: false
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license: other
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license_name: yi-license
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license_link: https://huggingface.co/01-ai/Yi-34B/blob/main/LICENSE
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metrics:
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- accuracy
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---
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This is the first [LASER](https://pratyushasharma.github.io/laser/) intervention on Pallas-0.5 .
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More will follow using the previous results as base.
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Configs used:
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- lnum: 59
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- lnames: attn (meaning: ["self_attn.k_proj.weight", "self_attn.q_proj.weight", "self_attn.v_proj.weight", "self_attn.o_proj.weight"])
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- rate: 6.0
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- dataset: bigbench (subset: causal_judgement)
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- intervention type: rank-reduction
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|Name|Validation acc (higher is better)|Validation logloss (lower is better)|Test acc (higher is better)|Test logloss (lower is better)|
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|Pallas-0.5|55.263|1.650|60.526|1.463|
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|Pallas-0.5-LASER-0.1|55.263|1.639|61.184|1.451|
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|Pallas-0.5-LASER-0.2|55.263|1.646|61.184|1.458|
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|Pallas-0.5-LASER-0.3|55.263|1.575|61.842|1.382|
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|Pallas-0.5-LASER-0.4|55.263|1.525|61.842|1.326|
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|Pallas-0.5-LASER-0.5|55.263|1.484|61.842|1.297|
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|Pallas-0.5-LASER-0.6|55.263|1.455|61.184|1.283|
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In order to replicate on a single A100, you can use [my branch](https://github.com/Mihaiii/laser/tree/allow-Yi-on-one-A100) (the original code will throw OOM for 34b models).
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