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Upload folder using huggingface_hub

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390M_4M_2k.csv ADDED
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390M_700kbs_10k.csv ADDED
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390M_700kbs_10k/blumodel_muon_4M_step00008001.pt ADDED
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+ oid sha256:3405f8d0554ccf6e5f902442e6e90ee381e3c61497b5e0cf1fa8de33276ec5bb
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+ size 4205803653
390M_700kbs_10k/blumodel_muon_4M_step00009000.pt ADDED
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390M_700kbs_10k/blumodel_muon_4M_step00009967.pt ADDED
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390M_700kbs_9k.csv ADDED
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train_390M.py CHANGED
@@ -448,9 +448,9 @@ class ModelConfig:
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  qk_eps: float = 1e-6 # QK-norm (fused) epsilon
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  # ---- optimization / data ----
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- B: int = 8 # micro-batch
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  T: int = 4096 # sequence length (<= context_length)
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- global_batch: int = 262144 # tokens per optimizer step
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  grad_clip: float = 1.0
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  weight_decay: float = 0.1
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@@ -463,7 +463,7 @@ class ModelConfig:
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  muon_lr: float = 0.001
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  muon_min_lr: float = 0.0001
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- max_steps: int = 53406
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  warmup_steps: int = 500
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  stable_steps: int = int(max_steps * 0.99) - warmup_steps # steps held at max_lr after warmup
 
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  qk_eps: float = 1e-6 # QK-norm (fused) epsilon
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  # ---- optimization / data ----
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+ B: int = 4 # micro-batch
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  T: int = 4096 # sequence length (<= context_length)
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+ global_batch: int = 786432 # tokens per optimizer step
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  grad_clip: float = 1.0
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  weight_decay: float = 0.1
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  muon_lr: float = 0.001
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  muon_min_lr: float = 0.0001
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+ max_steps: int = 17802
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  warmup_steps: int = 500
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  stable_steps: int = int(max_steps * 0.99) - warmup_steps # steps held at max_lr after warmup