Infos

Pythia-1b supervised finetuned with Anthropic-hh-rlhf dataset for 1 epoch (sft-model), before DPO (paper) with same dataset for 1 epoch.

wandb log

See Pythia-1b for model details (paper).

Benchmark raw results:

Results for the base model are taken from the Pythia paper.

Zero shot

Task 1B_base 1B_sft 1B_dpo
Lambada (OpenAI) 0.562 ± 0.007 0.563 ± 0.007 0.5575 ± 0.0069
PIQA 0.707 ± 0.011 0.711 ± 0.011 0.7122 ± 0.0106
WinoGrande 0.537 ± 0.014 0.534 ± 0.014 0.5525 ± 0.0140
WSC 0.365 ± 0.047 0.365 ± 0.047 0.3654 ± 0.0474
ARC - Easy 0.569 ± 0.010 0.583 ± 0.010 0.5901 ± 0.0101
ARC - Challenge 0.244 ± 0.013 0.248 ± 0.013 0.2611 ± 0.0128
SciQ 0.840 ± 0.012 0.847 ± 0.011 0.8530 ± 0.0112
LogiQA 0.223 ± 0.016 N/A N/A

Five shot

Task 1B_base 1B_sft 1B_dpo
Lambada (OpenAI) 0.507 ± 0.007 0.4722 ± 0.007 0.4669 ± 0.0070
PIQA 0.705 ± 0.011 0.7165 ± 0.0105 0.7138 ± 0.0105
WinoGrande 0.532 ± 0.014 0.5343 ± 0.014 0.5525 ± 0.0140
WSC 0.365 ± 0.047 0.5000 ± 0.0493 0.5577 ± 0.0489
ARC - Easy 0.594 ± 0.010 0.6010 ± 0.010 0.6170 ± 0.0100
ARC - Challenge 0.259 ± 0.013 0.2679 ± 0.0129 0.2833 ± 0.0132
SciQ 0.920 ± 0.009 0.9100 ± 0.0091 0.9020 ± 0.0094
LogiQA 0.227 ± 0.016 N/A N/A
Downloads last month
17
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Dataset used to train Leogrin/eleuther-pythia1b-hh-dpo