metadata
license: apache-2.0
tags:
- baseweight-benchmark
- benchmark
- predictions
Baseweight Benchmark — Raw Predictions
Every model generation produced during evaluation for the Baseweight Benchmark, a reproducible comparison of fine-tuned open models against frontier APIs on focused vertical tasks.
What's here
One JSONL file per model × task × condition × seed. Each line is one prediction:
| Field | Description |
|---|---|
id |
Row identifier from the prepared test split |
model |
Model short name (qwen3-8b, gpt-5.4-mini) |
condition |
lora, zero-shot, or 5-shot |
eval_seed |
Seed used for this eval run (0, 1, or 2) |
prompt_sha |
SHA-256 prefix of the prompt template used |
input |
The text input sent to the model |
output |
The raw model output |
ground_truth |
Gold label or answer |
input_tokens |
Prompt token count |
output_tokens |
Completion token count |
avg_logprob |
Mean log-probability of output tokens |
timestamp |
UTC time of the generation |
File layout
predictions/
local/
qwen3-8b/
banking77/ lora.jsonl lora_seed1.jsonl lora_seed2.jsonl
zero-shot.jsonl zero-shot_seed1.jsonl zero-shot_seed2.jsonl
5-shot.jsonl 5-shot_seed1.jsonl 5-shot_seed2.jsonl
cuad/ lora.jsonl lora_seed1.jsonl lora_seed2.jsonl
zero-shot.jsonl zero-shot_seed1.jsonl zero-shot_seed2.jsonl
api/
gpt-5.4-mini/
banking77/ zero-shot.jsonl zero-shot_seed1.jsonl zero-shot_seed2.jsonl
5-shot.jsonl 5-shot_seed1.jsonl 5-shot_seed2.jsonl
cuad/ zero-shot.jsonl zero-shot_seed1.jsonl zero-shot_seed2.jsonl
Seeds 1 and 2 are independent re-evaluations with shuffled test order. Seed 0 is the base run (file without seed suffix). Reported metrics are the mean across all three seeds; 95% CIs are bootstrap intervals over the seeds.
Verifying the numbers
Download any JSONL, recompute the metric against ground_truth, and compare
to the value in results.json on the benchmark site. The prompt_sha field
lets you confirm the exact prompt template used.
Links
- Benchmark site: baseweight.co/benchmark
- Pipeline code: github.com/baseweight-ai/benchmark
- Prepared data splits: baseweight-ai/baseweight-benchmark-data
- Fine-tuned adapters: baseweight-ai/baseweight-benchmark-adapters