Record: Adaptive Precision Embedding Quantization (4-seed mean val_bpb=1.1217)#1042
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nothingLiva wants to merge 6 commits intoopenai:mainfrom
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Record: Adaptive Precision Embedding Quantization (4-seed mean val_bpb=1.1217)#1042nothingLiva wants to merge 6 commits intoopenai:mainfrom
nothingLiva wants to merge 6 commits intoopenai:mainfrom
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"Hi! This is my first competition submission, so I'm not entirely sure about the process. Is there anything missing or needed from my side? Happy to address any feedback! 🙂" |
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Adaptive Precision Embedding Quantization
val_bpb: 1.1217 (4-seed mean) | 15.8 MB | 8×H100 SXM
Checklist
See README.md for full details
Key Innovation
Top 100 tokens cover 53% of all text. Instead of uniform int6 quantization, this applies:
Frequent tokens deserve more precision because their errors compound across the entire dataset.
Results (4 seeds, 8×H100 SXM)
Mean: 1.1217 | Std: 0.0005