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Add HRM-FBW-K3-H2-L3-H18-L15-causal-AdamATan2-EMA-seed0-fromHRM-epoch3-SrcL1-L3-H1-L4-L6-H2__20261007-004905_hrm-fbw-epoch3-rerun--wzacavn3 step 304578 weights

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  1. HRM-FBW-K3-H2-L3-H18-L15-causal-AdamATan2-EMA-seed0-fromHRM-epoch3-SrcL1-L3-H1-L4-L6-H2__20261007-004905_hrm-fbw-epoch3-rerun--wzacavn3/step_304578/README.md +16 -0
  2. HRM-FBW-K3-H2-L3-H18-L15-causal-AdamATan2-EMA-seed0-fromHRM-epoch3-SrcL1-L3-H1-L4-L6-H2__20261007-004905_hrm-fbw-epoch3-rerun--wzacavn3/step_304578/checkpoint_receipt.json +134 -0
  3. HRM-FBW-K3-H2-L3-H18-L15-causal-AdamATan2-EMA-seed0-fromHRM-epoch3-SrcL1-L3-H1-L4-L6-H2__20261007-004905_hrm-fbw-epoch3-rerun--wzacavn3/step_304578/config.json +263 -0
  4. HRM-FBW-K3-H2-L3-H18-L15-causal-AdamATan2-EMA-seed0-fromHRM-epoch3-SrcL1-L3-H1-L4-L6-H2__20261007-004905_hrm-fbw-epoch3-rerun--wzacavn3/step_304578/launch_config.env +5 -0
  5. HRM-FBW-K3-H2-L3-H18-L15-causal-AdamATan2-EMA-seed0-fromHRM-epoch3-SrcL1-L3-H1-L4-L6-H2__20261007-004905_hrm-fbw-epoch3-rerun--wzacavn3/step_304578/launch_config.yaml +3 -0
  6. HRM-FBW-K3-H2-L3-H18-L15-causal-AdamATan2-EMA-seed0-fromHRM-epoch3-SrcL1-L3-H1-L4-L6-H2__20261007-004905_hrm-fbw-epoch3-rerun--wzacavn3/step_304578/manifest.json +48 -0
  7. HRM-FBW-K3-H2-L3-H18-L15-causal-AdamATan2-EMA-seed0-fromHRM-epoch3-SrcL1-L3-H1-L4-L6-H2__20261007-004905_hrm-fbw-epoch3-rerun--wzacavn3/step_304578/model.safetensors +3 -0
  8. HRM-FBW-K3-H2-L3-H18-L15-causal-AdamATan2-EMA-seed0-fromHRM-epoch3-SrcL1-L3-H1-L4-L6-H2__20261007-004905_hrm-fbw-epoch3-rerun--wzacavn3/step_304578/original_model.safetensors +3 -0
  9. HRM-FBW-K3-H2-L3-H18-L15-causal-AdamATan2-EMA-seed0-fromHRM-epoch3-SrcL1-L3-H1-L4-L6-H2__20261007-004905_hrm-fbw-epoch3-rerun--wzacavn3/step_304578/tokenizer/tokenizer.json +0 -0
  10. HRM-FBW-K3-H2-L3-H18-L15-causal-AdamATan2-EMA-seed0-fromHRM-epoch3-SrcL1-L3-H1-L4-L6-H2__20261007-004905_hrm-fbw-epoch3-rerun--wzacavn3/step_304578/training_completion.json +63 -0
  11. HRM-FBW-K3-H2-L3-H18-L15-causal-AdamATan2-EMA-seed0-fromHRM-epoch3-SrcL1-L3-H1-L4-L6-H2__20261007-004905_hrm-fbw-epoch3-rerun--wzacavn3/step_304578/training_recipe.json +274 -0
HRM-FBW-K3-H2-L3-H18-L15-causal-AdamATan2-EMA-seed0-fromHRM-epoch3-SrcL1-L3-H1-L4-L6-H2__20261007-004905_hrm-fbw-epoch3-rerun--wzacavn3/step_304578/README.md ADDED
@@ -0,0 +1,16 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ # HRM-FBW-K3-H2-L3-H18-L15-causal-AdamATan2-EMA-seed0-fromHRM-epoch3-SrcL1-L3-H1-L4-L6-H2__20261007-004905_hrm-fbw-epoch3-rerun--wzacavn3
2
+
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+ Successful final epoch4 checkpoint, optimizer step304578; 1,232,342,016 parameters. Native weights-only export: model.safetensors contains EMA weights matching in-training reference evaluation; original_model.safetensors contains ordinary weights. Optimizer/RNG/data state stays in the local full checkpoint.
4
+
5
+ Native HRM epoch3 continuation source and full fourth-epoch K2/K3 curriculum are pinned in training_recipe.json/config.json. Six feedback sources are ['L1', 'L3', 'H1', 'L4', 'L6', 'H2']; evaluation depthK3. Preserve the original cycle-output interpretation, not physical layer numbering. Original W&B: https://wandb.ai/LoopTF-4-CSPs/causal_hrm_text/runs/wzacavn3. No unverified final autoregressive benchmark score is claimed.
6
+
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+ Use https://github.com/FFishy-git/loopTF-workspace/tree/24e8310581000309bad97cb807ed5857ab0d0c85 and pinned HRM-Text upstreamaaa948ea674fd84b7bc455c9cfb455ecfefdf914. This custom native model is not a Transformers AutoModel checkpoint. With dependencies installed:
8
+
9
+ import json
10
+ from safetensors.torch import load_file
11
+ from hrm_text_tf.official.evaluation.checkpoint import build_fbw_model
12
+ config = json.load(open('config.json'))
13
+ state = load_file('model.safetensors', device='cpu')
14
+ model = build_fbw_model(state, config['native_model_config'], '/path/to/pinned/HRM-Text', config['fbw']['num_passes'], tuple(config['fbw']['feedback_sources']))
15
+
16
+ The builder loads strictly with assign=True, preserving saved tensor dtypes and rebuilding rotary buffers. To use ordinary final weights, select original_model.safetensors. Tokenizer and special-token metadata are included. Full training recovery state is excluded.
HRM-FBW-K3-H2-L3-H18-L15-causal-AdamATan2-EMA-seed0-fromHRM-epoch3-SrcL1-L3-H1-L4-L6-H2__20261007-004905_hrm-fbw-epoch3-rerun--wzacavn3/step_304578/checkpoint_receipt.json ADDED
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+ {
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+ "epoch": 4,
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+ "epoch_step": 76143,
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+ "epoch_micro_step": 76143,
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+ "accumulation_steps": 1,
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+ "reference_replicas": 32,
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+ "gradient_reduction": "sum",
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+ "gradient_reference_replicas": 32,
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+ "gradient_scale": 1.0,
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+ "step": 304578,
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+ "input_tokens": 59692873068,
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+ "response_labels": 25612353450,
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+ "examples": 230796395,
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+ "debug_partial_epoch": false,
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+ "max_grad_norm": 1.0,
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+ "continuation": {
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+ "mode": "hrm_to_fbw",
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+ "checkpoint": "/apdcephfs_tj31/share_303214315/hunyuan/kenanchen/loopTF-workspace/output/causal_hrm_text/continuation_sources/ty8nbhn0/full_epoch_3/checkpoints/fsdp2_epoch_3",
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+ "preserve_optimizer": true,
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+ "preserve_ema": true,
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+ "curriculum": [
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+ {
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+ "start_update": 228436,
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+ "mixture": {
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+ "2": 1.0
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+ }
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+ },
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+ {
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+ "start_update": 274312,
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+ "mixture": {
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+ "2": 0.7,
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+ "3": 0.3
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+ }
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+ }
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+ ],
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+ "source_epoch": 3,
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+ "source_step": 228435,
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+ "source_world_size": 32,
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+ "source_recipe_sha256": "8e53dcb59af9678277550dfa2540f3f2e32268c9386fa8f42936e616d8c3307b",
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+ "checkpoint_metadata_sha256": "4898bea588e7717f169d4b648be3faee795b2b8f821815301a886fca132543dd",
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+ "source_run_name": "HRM-H2-L3-H18-L15-causal-AdamATan2-EMA-seed0-H800x32-20260925-002521",
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+ "source_wandb_run_id": "ty8nbhn0",
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+ "data_epoch_index": 3,
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+ "rng_restored": false,
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+ "bit_exact_resume": false
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+ },
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+ "architecture": {
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+ "arm": "hrm_fbw",
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+ "fbw": {
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+ "num_passes": 3,
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+ "feedback_sources": [
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+ "L1",
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+ "L3",
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+ "H1",
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+ "L4",
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+ "L6",
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+ "H2"
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+ ]
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+ },
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+ "hrm": {
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+ "h_layers": 18,
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+ "l_layers": 15,
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+ "h_cycles": 2,
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+ "l_cycles": 3
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+ },
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+ "forward_blocks": 378,
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+ "response_ce_weights": [
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+ 0.5,
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+ 0.25,
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+ 0.25
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+ ],
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+ "pass_schedule": null,
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+ "feedback": "shifted previous-pass latent, normalized FBW gate, reset at document starts",
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+ "inner_bp": "K1: upstream warmup; K>1: preceding passes max(5, scheduled BP), final pass full BP8",
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+ "feedback_source_fusion": {
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+ "operation": "concatenate_then_bias_free_linear",
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+ "initialization": "final_H2_identity",
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+ "states": "outputs of complete L/H stack invocations, including stack normalization",
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+ "projection_parameters": 14155776,
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+ "lm_head_source": "H2"
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+ }
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+ },
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+ "pass_schedule": {
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+ "progress": "absolute_optimizer_updates",
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+ "stages": [
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+ {
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+ "mixture": {
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+ }
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+ },
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+ {
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+ "mixture": {
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+ "2": 0.7,
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+ }
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+ }
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+ ],
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+ "estimated_total_steps": 304789,
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+ "seed": 0,
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+ "sampler": "sha256-counter-v1",
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+ "step_convention": "completed updates before the next update; first update uses zero",
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+ "start_completed_updates": [
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+ 228435,
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+ 274311
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+ ],
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+ "first_update_per_stage": [
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+ 228436,
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+ 274312
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+ ],
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+ "after_horizon": "keep final mixture"
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+ },
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+ "pass_accounting": {
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+ "1": {
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+ "updates": 228435,
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+ "input_tokens": 44769895151,
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+ "response_labels": 19208956003,
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+ "examples": 173097293
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+ },
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+ "2": {
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+ "input_tokens": 13140065044,
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+ "response_labels": 5638502351,
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+ "3": {
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+ "input_tokens": 1782912873,
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+ "response_labels": 764895096,
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+ }
HRM-FBW-K3-H2-L3-H18-L15-causal-AdamATan2-EMA-seed0-fromHRM-epoch3-SrcL1-L3-H1-L4-L6-H2__20261007-004905_hrm-fbw-epoch3-rerun--wzacavn3/step_304578/config.json ADDED
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+ {
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+ "architecture": "hrm_fbw",
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+ "architecture_receipt": {
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+ "arm": "hrm_fbw",
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+ "fbw": {
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+ "feedback_sources": [
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+ "L1",
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+ "L3",
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+ "H1",
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+ "L4",
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+ "L6",
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+ "H2"
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+ ],
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+ "num_passes": 3
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+ },
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+ "feedback": "shifted previous-pass latent, normalized FBW gate, reset at document starts",
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+ "feedback_source_fusion": {
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+ "initialization": "final_H2_identity",
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+ "lm_head_source": "H2",
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+ "operation": "concatenate_then_bias_free_linear",
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+ "projection_parameters": 14155776,
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+ "states": "outputs of complete L/H stack invocations, including stack normalization"
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+ },
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+ "forward_blocks": 378,
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+ "hrm": {
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+ "h_cycles": 2,
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+ "h_layers": 18,
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+ "l_cycles": 3,
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+ "l_layers": 15
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+ },
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+ "inner_bp": "K1: upstream warmup; K>1: preceding passes max(5, scheduled BP), final pass full BP8",
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+ "lookahead": null,
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+ "pass_schedule": null,
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+ "response_ce_weights": [
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+ 0.5,
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+ 0.25,
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+ 0.25
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+ ]
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+ },
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+ "checkpoint_format": "safetensors_native_hrm_fbw_state_dict",
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+ "continuation": {
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+ "bit_exact_resume": false,
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+ "checkpoint": "/apdcephfs_tj31/share_303214315/hunyuan/kenanchen/loopTF-workspace/output/causal_hrm_text/continuation_sources/ty8nbhn0/full_epoch_3/checkpoints/fsdp2_epoch_3",
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+ "checkpoint_metadata_sha256": "4898bea588e7717f169d4b648be3faee795b2b8f821815301a886fca132543dd",
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+ }
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+ ],
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+ "data_epoch_index": 3,
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+ "mode": "hrm_to_fbw",
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+ "preserve_ema": true,
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+ "preserve_optimizer": true,
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+ "rng_restored": false,
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+ "source_epoch": 3,
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+ "source_recipe_sha256": "8e53dcb59af9678277550dfa2540f3f2e32268c9386fa8f42936e616d8c3307b",
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+ "source_run_name": "HRM-H2-L3-H18-L15-causal-AdamATan2-EMA-seed0-H800x32-20260925-002521",
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+ "source_step": 228435,
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+ "source_wandb_run_id": "ty8nbhn0",
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+ "source_world_size": 32
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+ },
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+ "dtype": "preserved per tensor from source checkpoint",
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+ "epoch": 4,
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+ "eval_num_passes": 3,
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+ "export_code_revision": "24e8310581000309bad97cb807ed5857ab0d0c85",
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+ "fbw": {
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+ "L1",
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+ "H1",
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+ "L4",
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+ "L6",
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+ "H2"
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+ ],
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+ "num_passes": 3
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+ },
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+ "iteration": 304578,
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+ "native_model_config": {
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+ "H_cycles": 2,
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+ "H_override": {
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+ },
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+ "L_cycles": 3,
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+ "attn_type": "causal",
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+ "bp_max_steps": 5,
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+ "bp_warmup_ratio": 0.2,
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+ "expansion": 4,
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+ "half_layers": false,
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+ "head": "lm_head@LMHead",
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+ "init_type": "lecun_normal",
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+ "max_seq_len": 4096,
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+ "n_layers": 15,
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+ "name": "baselines.hrm_nocarry_bp_warmup@HierarchicalReasoningModel",
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+ "norm_type": "pre",
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+ "pos_emb_type": "rope",
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+ "rope_theta": 10000.0,
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+ "vocab_size": 65536
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+ },
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+ "ordinary_weights_file": "original_model.safetensors",
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+ "original_training_run_name": "HRM-FBW-K3-H2-L3-H18-L15-causal-AdamATan2-EMA-seed0-fromHRM-epoch3-SrcL1-L3-H1-L4-L6-H2__20261007-004905_hrm-fbw-epoch3-rerun",
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+ "run_name": "HRM-FBW-K3-H2-L3-H18-L15-causal-AdamATan2-EMA-seed0-fromHRM-epoch3-SrcL1-L3-H1-L4-L6-H2__20261007-004905_hrm-fbw-epoch3-rerun--wzacavn3",
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+ "source_checkpoint": "/apdcephfs_tj31/share_303214315/hunyuan/kenanchen/loopTF-workspace/output/launchings/20261007-004905_hrm-fbw-epoch3-rerun/HRM-FBW-K3-H2-L3-H18-L15-causal-AdamATan2-EMA-seed0-fromHRM-epoch3-SrcL1-L3-H1-L4-L6-H2__20261007-004905_hrm-fbw-epoch3-rerun/checkpoints/fsdp2_epoch_4",
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+ "source_metadata_sha256": "159c5528d402be1f6382ffb16cb6d4578075d3540249e93c5697732ee512b80e",
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+ "source_wandb": {
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+ "entity": "LoopTF-4-CSPs",
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+ "group": "official_recipe",
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+ "history_step": 304575,
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+ "history_step_offset": 0,
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+ "id": "wzacavn3",
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+ "name": "HRM-FBW-K3-H2-L3-H18-L15-causal-AdamATan2-EMA-seed0-fromHRM-epoch3-SrcL1-L3-H1-L4-L6-H2__20261007-004905_hrm-fbw-epoch3-rerun",
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+ "project": "causal_hrm_text",
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+ "tags": [
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+ "product",
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+ "causal_hrm_text",
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+ "official_recipe",
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+ "hrm_fbw",
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+ "flex_causal",
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+ "h800",
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+ "resume",
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+ "hrm_to_fbw",
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+ "six_sources",
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+ "epoch4",
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+ "progressive_passes",
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+ "optimized",
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+ "selective_recompute",
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+ "model_fsdp",
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+ "k2_two_thirds_retention",
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+ "rerun_from_epoch3",
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+ "progressive_passes"
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+ ],
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+ "url": "https://wandb.ai/LoopTF-4-CSPs/causal_hrm_text/runs/wzacavn3"
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+ },
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+ "tensor_parallel_size": 1,
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+ "tokenizer_info": {
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+ "boq": "<|im_start|>",
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+ "cot": "<|object_ref_end|>",
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+ "direct": "<|object_ref_start|>",
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+ "noisy": "<|quad_start|>",
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+ "synth": "<|quad_end|>"
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+ },
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+ "eoa": "<|box_end|>",
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+ "eoq": "<|im_end|>",
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+ "tokenizer_path": "/root/dl/runtime/script/loopTF-workspace/data/causal_hrm_text_sources/data_io/trained_tokenizers/bpe/tokenizer.json",
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+ "vocab_size": 65536
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