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Pythia-1.4b supervised finetuned with Anthropic-hh-rlhf dataset for 1 epoch (sft-model), before DPO (paper) with same dataset for 1 epoch.
See Pythia-1.4b for model details (paper).
Benchmark raw results:
Results for the base model are taken from the Pythia paper.
Zero shot
Task | 1.4B_base | 1.4B_sft | 1.4B_dpo |
---|---|---|---|
Lambada (OpenAI) | 0.616 ± 0.007 | 0.5977 ± 0.0068 | 0.5948 ± 0.0068 |
PIQA | 0.711 ± 0.011 | 0.7133 ± 0.0106 | 0.7165 ± 0.0105 |
WinoGrande | 0.573 ± 0.014 | 0.5793 ± 0.0139 | 0.5746 ± 0.0139 |
WSC | 0.365 ± 0.047 | 0.3654 ± 0.0474 | 0.3654 ± 0.0474 |
ARC - Easy | 0.606 ± 0.010 | 0.6098 ± 0.0100 | 0.6199 ± 0.0100 |
ARC - Challenge | 0.260 ± 0.013 | 0.2696 ± 0.0130 | 0.2884 ± 0.0132 |
SciQ | 0.865 ± 0.011 | 0.8540 ± 0.0112 | 0.8550 ± 0.0111 |
LogiQA | 0.210 ± 0.016 | NA | NA |
Five shot
Task | 1.4B_base | 1.4B_sft | 1.4B_dpo |
---|---|---|---|
Lambada (OpenAI) | 0.578 ± 0.007 | 0.5201 ± 0.007 | 0.5247 ± 0.007 |
PIQA | 0.705 ± 0.011 | 0.7176 ± 0.0105 | 0.7209 ± 0.0105 |
WinoGrande | 0.580 ± 0.014 | 0.5793 ± 0.0139 | 0.5746 ± 0.0139 |
WSC | 0.365 ± 0.047 | 0.5288 ± 0.0492 | 0.5769 ± 0.0487 |
ARC - Easy | 0.643 ± 0.010 | 0.6376 ± 0.0099 | 0.6561 ± 0.0097 |
ARC - Challenge | 0.290 ± 0.013 | 0.2935 ± 0.0133 | 0.3166 ± 0.0136 |
SciQ | 0.92 ± 0.009 | 0.9180 ± 0.0087 | 0.9150 ± 0.0088 |
LogiQA | 0.240 ± 0.017 | N/A | N/A |
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