results
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README.md
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AI Model Name: Llama 3 8B "Built with Meta Llama 3" https://llama.meta.com/llama3/license/
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Full walkthrough to reproduce these results here: https://github.com/catid/AQLM/blob/main/catid_readme.md
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AI Model Name: Llama 3 8B "Built with Meta Llama 3" https://llama.meta.com/llama3/license/
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Full walkthrough to reproduce these results here: https://github.com/catid/AQLM/blob/main/catid_readme.md
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Baseline evaluation results:
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```
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hf (pretrained=meta-llama/Meta-Llama-3-8B-Instruct), gen_kwargs: (None), limit: None, num_fewshot: None, batch_size: 16
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| Tasks |Version|Filter|n-shot| Metric |Value | |Stderr|
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|-------------|------:|------|-----:|--------|-----:|---|-----:|
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|winogrande | 1|none | 0|acc |0.7198|± |0.0126|
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|piqa | 1|none | 0|acc |0.7873|± |0.0095|
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| | |none | 0|acc_norm|0.7867|± |0.0096|
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|hellaswag | 1|none | 0|acc |0.5767|± |0.0049|
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| | |none | 0|acc_norm|0.7585|± |0.0043|
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|arc_easy | 1|none | 0|acc |0.8140|± |0.0080|
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| | |none | 0|acc_norm|0.7971|± |0.0083|
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|arc_challenge| 1|none | 0|acc |0.5290|± |0.0146|
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| | |none | 0|acc_norm|0.5674|± |0.0145|
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```
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This repo evaluation results (AQLM with global fine-tuning):
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```
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hf (pretrained=catid/cat-llama-3-8b-instruct-aqlm), gen_kwargs: (None), limit: None, num_fewshot: None, batch_size: 16
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| Tasks |Version|Filter|n-shot| Metric |Value | |Stderr|
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|-------------|------:|------|-----:|--------|-----:|---|-----:|
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|winogrande | 1|none | 0|acc |0.7119|± |0.0127|
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|piqa | 1|none | 0|acc |0.7807|± |0.0097|
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| | |none | 0|acc_norm|0.7824|± |0.0096|
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|hellaswag | 1|none | 0|acc |0.5716|± |0.0049|
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| | |none | 0|acc_norm|0.7539|± |0.0043|
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|arc_easy | 1|none | 0|acc |0.8152|± |0.0080|
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| | |none | 0|acc_norm|0.7866|± |0.0084|
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|arc_challenge| 1|none | 0|acc |0.5043|± |0.0146|
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| | |none | 0|acc_norm|0.5555|± |0.0145|
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```
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To reproduce evaluation results:
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```bash
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git clone https://github.com/EleutherAI/lm-evaluation-harness
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cd lm-evaluation-harness
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conda create -n lmeval python=3.10 -y && conda activate lmeval
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pip install -e .
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pip install accelerate aqlm"[gpu,cpu]"
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accelerate launch lm_eval --model hf \
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--model_args pretrained=catid/cat-llama-3-8b-instruct-aqlm \
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--tasks winogrande,piqa,hellaswag,arc_easy,arc_challenge \
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--batch_size 16
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```
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You can run this model as a `transformers` model using https://github.com/oobabooga/text-generation-webui
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