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Michael J Clark
2024-02-03 14:02:27 +08:00
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@@ -2,9 +2,14 @@ My own experiments with DLK
- [x] use pytorch lightning
- [x] batch hidden states 5x faster
- [ ] use llama 13B, to see if larger models give better results
- [ ] eval on some deceptive or misleading statements
- [ ] debug by looking at model output
- [x] use llama 13B, to see if larger models give better results
- [x] eval on some deceptive or misleading statements
- [x] debug by looking at model output
- [x] try ranking hidden state (on a branch)
- [x] try a tokenized autoencoder (on a branch)
- [x] try a sparse autoencoder (on a branch)
I'm afraid none of these approaches have got the >90% out of distribution results I hope for. I beleive this to be because current models are too small to have internals that reliably produce deception.
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