Infos
Pythia-1.4b supervised finetuned with Anthropic-hh-rlhf 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 |
---|---|---|
Lambada (OpenAI) | 0.616 ± 0.007 | 0.5977 ± 0.0068 |
PIQA | 0.711 ± 0.011 | 0.7133 ± 0.0106 |
WinoGrande | 0.573 ± 0.014 | 0.5793 ± 0.0139 |
WSC | 0.365 ± 0.047 | 0.3654 ± 0.0474 |
ARC - Easy | 0.606 ± 0.010 | 0.6098 ± 0.0100 |
ARC - Challenge | 0.260 ± 0.013 | 0.2696 ± 0.0130 |
SciQ | 0.865 ± 0.011 | 0.8540 ± 0.0112 |
LogiQA | 0.210 ± 0.016 | NA |
Five shot
Task | 1.4B_base | 1.4B_sft |
---|---|---|
Lambada (OpenAI) | 0.578 ± 0.007 | 0.5201 ± 0.007 |
PIQA | 0.705 ± 0.011 | 0.7176 ± 0.0105 |
WinoGrande | 0.580 ± 0.014 | 0.5793 ± 0.0139 |
WSC | 0.365 ± 0.047 | 0.5288 ± 0.0492 |
ARC - Easy | 0.643 ± 0.010 | 0.6376 ± 0.0099 |
ARC - Challenge | 0.290 ± 0.013 | 0.2935 ± 0.0133 |
SciQ | 0.92 ± 0.009 | 0.9180 ± 0.0087 |
LogiQA | 0.240 ± 0.017 | N/A |
- Downloads last month
- 15
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.