End of pre-training era for language models: Will an LM fine-tune for more FLOPs than it is pre-trained for, before 2026
IAOne-Off2m
Manifold MarketsSin KYCDatos de resolución verificadosCalibración aceptablePronóstico comunitario actual
No 63.2%
No 63.2%Pronosticadores
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Tipo de pregunta
binary
Metodología
Play-money forecasting platform
Tipo de fuente
Pronóstico
Datos de mercado
Actualizado hace 17 horas
Desactualizado5 may 23, 23:06 UTC2 ene 27, 4:59 UTC
Tendencias
Reglas
The LM must have 'frontier' performance (having PILE/or similar perplexity above one year prior's SotA).
- The LM must have been trained after 2022.
- If it's unclear whether this has happened, I will give this a year to resolve.
- If it remains plausibly unclear the market will resolve N/A. Fine-tuning includes all RL training.
- Training on synthetic data, or additional supervised learning (which is deliberately trained on after training on a PILE-like generic dataset) counts as fine-tuning.
