1.4 KiB
2025-02-17 17:39:09
My supressed activation experiment on 3b and 7b models worked
TODO
- Graph
- Try other formulation of supression
- Mark each neuron?
- Graph by token?
- check the projections are communtitive and reversible!?
- stats on supressed neurons (histogram)
- what about multi layer decoder, other datasets, more samples
3B model LLM score: 0.53 roc auc, n=116
name score
3 hs_sup last 0.639881 17 supressed_mask none 0.631845 15 supressed_mask last 0.626786 1 hs_sup max 0.619643 11 hidden_states none 0.617559 0 hs_sup mean 0.615476 2 hs_sup sum 0.615476 8 hidden_states sum 0.608333 6 hidden_states mean 0.608333 5 hs_sup none 0.602679 16 supressed_mask first 0.601786 10 hidden_states first 0.594345 4 hs_sup first 0.572024 9 hidden_states last 0.557143 14 supressed_mask sum 0.554762 12 supressed_mask mean 0.554762 7 hidden_states max 0.541964 13 supressed_mask max 0.496726
0.5b model LLM score: 0.54 roc auc, n=116
name score
33 hs_sup none last 0.769643 23 hs_sup last none 0.769643 100 hidden_states none mean 0.755059 93 hidden_states last none 0.755059 87 hidden_states sum none 0.755059 105 hidden_states none none 0.755059 103 hidden_states none last 0.755059 102 hidden_states none sum 0.755059 99 hidden_states first none 0.754762 101 hidden_states none max 0.754762 75 hidden_states mean none 0.754464 104 hidden_states none first 0.754464 81 hidden_states max none 0.754167 11 hs_sup max none 0.753274