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---
license: other
datasets:
- JeanKaddour/minipile
language:
- en
---
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).
Layers to prune selected using [PruneMe](https://github.com/arcee-ai/PruneMe).
Still evaluating, don't get too excited! Might be incredibly dumb. Check out these zero-shot MMLU numbers though:
| Groups |Version|Filter|n-shot|Metric|Value | |Stderr|
|------------------|-------|------|-----:|------|-----:|---|-----:|
|mmlu |N/A |none | 0|acc |0.7319|± |0.0034|
| - humanities |N/A |none | 0|acc |0.6582|± |0.0063|
| - other |N/A |none | 0|acc |0.7927|± |0.0069|
| - social_sciences|N/A |none | 0|acc |0.8466|± |0.0064|
| - stem |N/A |none | 0|acc |0.6702|± |0.0079|
5-shot:
| Groups |Version|Filter|n-shot|Metric|Value | |Stderr|
|------------------|-------|------|-----:|------|-----:|---|-----:|
|mmlu |N/A |none | 0|acc |0.7669|± |0.0034|
| - humanities |N/A |none | 5|acc |0.7296|± |0.0062|
| - other |N/A |none | 5|acc |0.8101|± |0.0067|
| - social_sciences|N/A |none | 5|acc |0.8668|± |0.0060|
| - stem |N/A |none | 5|acc |0.6825|± |0.0079| |