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- Num weight bits = 18
- learning rate = 0.5
- initial_t = 0
- power_t = 0.5
- using no cache
- Reading datafile = train-adf.dat
- num sources = 1
- Enabled reductions: gd, generate_interactions, scorer-identity, csoaa_ldf-rank, cb_adf, cb_explore_adf_greedy, cb_sample, shared_feature_merger, ccb_explore_adf
- Input label = ccb
- Output pred = decision_probs
- average since example example current current current
- loss last counter weight label predict features
- [warning] Unlabeled example in train set, was this intentional?
- 0.000000 0.000000 1 1.0 ?,1:0.8 0,1 72
- finished run
- number of examples = 1
- weighted example sum = 1.000000
- weighted label sum = 0.000000
- average loss = 0.000000
- total feature number = 72
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