{ "repo": "OpenCoder-LLM/OpenCoder-1.5B-Base-Checkpoints", "tokens_per_step": 4194304, "pretrain_steps": [ 1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000, 10000, 11000, 12000, 13000, 14000, 15000, 16000, 17000, 18000, 19000, 20000, 21000, 22000, 23000, 24000, 25000, 26000, 27000, 28000, 29000, 30000, 31000, 32000, 33000, 34000, 35000, 36000, 37000, 38000, 39000, 40000, 41000, 42000, 43000, 44000, 45000, 46000, 47000, 48000, 49000, 50000, 51000, 52000, 53000, 54000, 55000, 56000, 57000, 58000, 59000, 60000, 61000, 62000, 63000, 64000, 65000, 66000, 67000, 68000, 69000, 70000, 71000, 72000, 73000, 74000, 75000, 76000, 77000, 78000, 79000, 80000, 81000, 82000, 83000, 84000, 85000, 86000, 87000, 88000, 89000, 90000, 91000, 92000, 93000, 94000, 95000, 96000, 97000, 98000, 99000, 100000, 101000, 102000, 103000, 104000, 105000, 106000, 107000, 108000, 109000, 110000, 111000, 112000, 113000, 114000, 115000, 116000, 117000, 118000, 119000, 120000, 121000, 122000, 123000, 124000, 125000, 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16000, 17000, 18000, 19000, 20000, 21000, 22000, 23000, 23841 ], "fork_step": 373000, "final_base_anneal_step": 23000, "last_pretrain_tokens": 2033671208960, "learning_rate_values": { "standing": "measured from the tech report, 1 Oct 2026 (item 6's owed literature item)", "source": "OpenCoder: The Open Cookbook for Top-Tier Code Large Language Models, arXiv:2411.04905v3, section 3 training details, the 1.5B paragraph", "schedule": "WSD (warmup-stable-decay), after MiniCPM (Hu et al. 2024)", "warmup_steps": 2000, "warmup_tokens_reported": 8000000000.0, "warmup_tokens_computed": 8388608000, "peak_lr": 0.0003, "stable_lr": 0.0003, "stable_note": "constant at the peak after warm-up, for the whole pretraining branch", "anneal_final_lr": 1e-05, "anneal_decay": "exponential, during the annealing phase only", "global_batch": 1024, "micro_batch": 4, "sequence_length": 4096, "tokens_per_step_from_report": 4194304, "epochs": 4, "pretrain_tokens_reported": 2000000000000.0, "anneal_tokens_reported": 100000000000.0 }, "learning_rate_note": "Measured 1 Oct. The schedule is WSD: 2,000 steps of warm-up to 3e-4, then CONSTANT at 3e-4 for 99.6% of the pretraining branch, and the exponential decay to 1e-5 happens only on the annealing branch. So there is no learning-rate drop inside the pretraining branch for C8's bend to align with, and C8's first clause is vacuous as written -- see deviation A11. Two further facts the schedule forces: the first reference, step 1,000 = 4.19B, sits INSIDE the warm-up, half way through it, at an LR of about 1.5e-4 and still rising -- it is not a constant-LR point; and the 2.0337T branch is four epochs over about 508B unique tokens, so the fork at 1.5645T is 8% into the fourth epoch while every dense reference at or below 84B is in the first. Tokens per step from the report, 1024 x 4096 = 4,194,304, equals the measured figure exactly.", "reference_set": { "dense": [ 1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000, 10000, 11000, 12000, 13000, 14000, 15000, 16000, 17000, 18000, 19000, 20000 ], "tail": [ 25000, 31000, 39000, 49000, 61000, 76000, 95000, 119000, 149000, 186000, 233000, 291000, 364000, 455000, 484865 ], "anneal": [ 1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000, 10000, 11000, 12000, 13000, 14000, 15000, 16000, 17000, 18000, 19000, 20000, 21000, 22000, 23000, 23841 ], "n": 59 }, "epochs": { "n": 4, "tokens_per_epoch": 508417802240.0, "boundaries_tokens": [ 508417802240.0, 1016835604480.0, 1525253406720.0 ], "fork_epoch": 4, "dense_references_all_in_epoch": 1 } }