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--- |
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license: other |
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datasets: |
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- JeanKaddour/minipile |
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language: |
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- en |
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tags: |
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- axolotl |
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- mergekit |
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- llama |
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--- |
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> 🚨 THIS IS A BASE MODEL 🚨 |
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> |
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> This model is pruned from the base Llama 3 70B, which has no instruction tuning and randomly initialized special tokens. |
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> |
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> Using this with the Llama 3 instruction format is injecting random noise into latent space and will give you deranged results. (It's pretty funny actually.) |
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> Treat this as the untrained foundation model this is and use appropriate prompts. |
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Meta's Llama 3 70B pruned to 42B parameters using the methodology described in [The Unreasonable Ineffectiveness of the Deeper Layers](https://arxiv.org/abs/2403.17887). Post-pruning trained using QLoRA for ~100M tokens from [JeanKaddour/minipile](https://huggingface.co/datasets/JeanKaddour/minipile). |
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Layers to prune selected using [PruneMe](https://github.com/arcee-ai/PruneMe). |
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Still evaluating, don't get too excited! Might be incredibly dumb. Check out these numbers though: |
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| Groups |Version|Filter|n-shot|Metric|Value | |Stderr| |
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|------------------|-------|------|-----:|------|-----:|---|-----:| |
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|mmlu |N/A |none | 0|acc |0.7669|± |0.0034| |
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| - humanities |N/A |none | 5|acc |0.7296|± |0.0062| |
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| - other |N/A |none | 5|acc |0.8101|± |0.0067| |
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| - social_sciences|N/A |none | 5|acc |0.8668|± |0.0060| |
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| - stem |N/A |none | 5|acc |0.6825|± |0.0079| |
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|winogrande| 1|none | 5|acc |0.8027|± |0.0112| |
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|hellaswag| 1|none | 10|acc_norm|0.8025|± |0.0040| |
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[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl) |
