From 0590df1e88e39a53b3a0e3c0b71b7183c3627f12 Mon Sep 17 00:00:00 2001 From: Xin Wang Date: Wed, 26 Aug 2026 16:30:48 +0800 Subject: [PATCH] Record EasyCom loss structure ablation --- README.md | 13 ++ .../README.md | 117 ++++++++++++++++++ .../metrics.csv | 31 +++++ .../raw_console.txt | 59 +++++++++ .../summary.json | 105 ++++++++++++++++ 5 files changed, 325 insertions(+) create mode 100644 results/easycom_loss_structure_4ep_2026-08-26/README.md create mode 100644 results/easycom_loss_structure_4ep_2026-08-26/metrics.csv create mode 100644 results/easycom_loss_structure_4ep_2026-08-26/raw_console.txt create mode 100644 results/easycom_loss_structure_4ep_2026-08-26/summary.json diff --git a/README.md b/README.md index e21773e..44822df 100644 --- a/README.md +++ b/README.md @@ -147,6 +147,19 @@ Treat this as a capacity ablation. If it improves, compare it against a parameter-matched single-layer MLP and use stronger regularization or a clean development session before attributing the gain to cross-layer fusion. +#### Four-epoch loss-structure ablation + +Using the same frozen 8-second last-4 stack and concat-MLP readout, a +three-seed fixed-budget comparison tested LSTR-MCE, independent sigmoid/BCE, +and four-state softmax. All nine training sessions were used for exactly four +epochs with no development set. On the causal-valid test metric, no objective +is a decisive winner: BCE has the highest mean mAP (`60.91733`), while +four-state CE has the highest 0.2-second wearer AP (`78.72040`). Relative to +LSTR-MCE, both alternatives slightly improve the two speech classes while +reducing background AP. The full protocol, per-seed summary, seed-0 horizon +curves, and machine-readable data are archived in +[`results/easycom_loss_structure_4ep_2026-08-26/`](results/easycom_loss_structure_4ep_2026-08-26/README.md). + ## Current Ego4D context-length results The following single-seed snapshot was recorded on 2026-08-22. Both variants diff --git a/results/easycom_loss_structure_4ep_2026-08-26/README.md b/results/easycom_loss_structure_4ep_2026-08-26/README.md new file mode 100644 index 0000000..efcda66 --- /dev/null +++ b/results/easycom_loss_structure_4ep_2026-08-26/README.md @@ -0,0 +1,117 @@ +# EasyCom four-epoch loss-structure ablation + +Recorded on **2026-08-26** from user-reported remote +`train_turn_head.py`/`infer_turn_head.py` results. This experiment tests +whether the three-column EgoSpeak target is better modeled as competing +softmax classes, independent binary marginals, or four mutually exclusive +speech-activity states. + +## Experiment contract + +- Dataset: EasyCom. +- Train split: Sessions 4--12, all used for training. +- Development split: none. +- Test split: official Sessions 3, 2, and 1. +- Backbone: frozen Qwen2.5-Omni-3B Thinker. +- Streaming representation: 8-second open-stream replay, 2 FPS video, final + four query-layer states stacked at each 5 Hz target step. +- Readout: `concat-mlp`, followed by the anticipation MLP. +- Training budget: exactly 4 epochs for every objective. +- Reported command schedule: Adam, batch size 512, learning rate `7e-5`, + weight decay `5e-5`, dropout `0.2`, warmup factor `0.3`, and 1.6 warmup + epochs (the same 40% warmup fraction as the earlier 10/25 protocol). +- Seeds: 0, 1, and 2. +- Evaluation: `causal_valid_only` AP/mAP over ten future horizons from 0.2 to + 2.0 seconds. + +The objectives are: + +1. `lstr-mce`: three softmax logits with the original multi-positive MCE. +2. `independent-bce`: three independent sigmoid/BCE marginal labels. +3. `four-state-ce`: softmax over silence, wearer-only, others-only, and + overlap; evaluation marginalizes back to the original three labels. + +## Three-seed summary + +All values are percentage AP points, reported as mean +/- sample standard +deviation. + +| Objective | 0.2s mAP | 0.2s wearer AP | 0.2s others AP | 10-horizon mean mAP | +|---|---:|---:|---:|---:| +| LSTR-MCE | 73.70581 +/- 0.23802 | 78.41206 +/- 0.48622 | 85.74830 +/- 0.03661 | 60.81597 +/- 0.06941 | +| Independent BCE | 73.70702 +/- 0.08593 | 78.58842 +/- 0.16884 | 86.01169 +/- 0.09991 | **60.91733 +/- 0.03540** | +| Four-state CE | **73.81030 +/- 0.05499** | **78.72040 +/- 0.14753** | **86.03151 +/- 0.06097** | 60.88488 +/- 0.05728 | + +Relative to LSTR-MCE, four-state CE changes 0.2-second mAP by only +`+0.10449`, wearer AP by `+0.30834`, others AP by `+0.28321`, and mean mAP by +`+0.06891`. Independent BCE changes the same metrics by `+0.00121`, +`+0.17636`, `+0.26339`, and `+0.10136`, respectively. + +## Individual runs + +| Run | 0.2s mAP | Background AP | Wearer AP | Others AP | Mean mAP | +|---|---:|---:|---:|---:|---:| +| four-state-ce seed 0 | 73.74955 | 56.71375 | 78.57366 | 85.96124 | 60.83261 | +| four-state-ce seed 1 | 73.85667 | 56.63089 | 78.86871 | 86.07041 | 60.94612 | +| four-state-ce seed 2 | 73.82467 | 56.69228 | 78.71884 | 86.06288 | 60.87591 | +| independent-bce seed 0 | 73.62153 | 56.53017 | 78.40881 | 85.92561 | 60.87646 | +| independent-bce seed 1 | 73.79339 | 56.64809 | 78.74388 | 85.98820 | 60.93730 | +| independent-bce seed 2 | 73.70613 | 56.38458 | 78.61257 | 86.12125 | 60.93824 | +| lstr-mce seed 0 | 73.44637 | 56.76438 | 77.86650 | 85.70824 | 60.84861 | +| lstr-mce seed 1 | 73.75696 | 56.94418 | 78.57004 | 85.75664 | 60.73626 | +| lstr-mce seed 2 | 73.91410 | 57.16263 | 78.79964 | 85.78001 | 60.86305 | + +## Seed-0 horizon comparison + +| Horizon | LSTR-MCE mAP | Independent BCE mAP | Four-state CE mAP | +|---:|---:|---:|---:| +| 0.2s | 73.44637 | 73.62153 | 73.74955 | +| 0.4s | 68.63790 | 68.93990 | 68.82697 | +| 0.6s | 64.64750 | 64.79984 | 64.80523 | +| 0.8s | 61.50690 | 61.57880 | 61.52546 | +| 1.0s | 59.35000 | 59.53538 | 59.44807 | +| 1.2s | 58.08335 | 57.95764 | 57.96347 | +| 1.4s | 57.22382 | 56.94317 | 56.95413 | +| 1.6s | 56.15409 | 56.04943 | 55.84352 | +| 1.8s | 55.11616 | 55.09841 | 54.89116 | +| 2.0s | 54.32006 | 54.24044 | 54.31858 | +| **Mean** | **60.84861** | **60.87646** | **60.83261** | + +The complete seed-0 class AP curves are stored in [`metrics.csv`](metrics.csv) +and [`summary.json`](summary.json). + +## Interpretation + +This is not a clear aggregate improvement. The two non-competing objectives +slightly improve wearer/others ranking, but generally trade away background +ranking. Four-state CE is best for the pre-specified short-horizon wearer +metric, while independent BCE is marginally best for ten-horizon mean mAP. +The differences are small relative to seed variation, and four-state CE does +not establish a decisive advantage over the simpler BCE formulation. + +The defensible paper statement is therefore: + +> Non-competing label formulations provide small speech-class gains under a +> fixed four-epoch budget, but no loss formulation significantly dominates +> aggregate anticipation mAP. + +Before interpreting this as an overlap-modeling result, evaluate overlap AP +and per-session paired differences from the saved predictions. Because no dev +set was used, these results describe a fixed-compute ablation rather than each +objective's independently optimized performance. Do not select a primary loss +post hoc from these test results. + +## Provenance + +- Feature root: + `/data1/yfzx/wangx/Datasets/easycom/omni_features/open_stream_2fps_8s_last4_stack` +- Target root: + `/data1/yfzx/wangx/Datasets/easycom/easycom_target_frame` +- Remote checkpoint root: `checkpoints/easycom_loss_structure_4ep` +- Remote result root: `results/easycom_loss_structure_4ep` +- Full per-horizon output supplied for seed 0 only. +- Three-seed aggregate and individual-run summaries supplied for all losses. +- Raw remote checkpoint JSON and `metrics.json` files archived locally: no. + +Machine-readable records: [`summary.json`](summary.json), +[`metrics.csv`](metrics.csv), and [`raw_console.txt`](raw_console.txt). diff --git a/results/easycom_loss_structure_4ep_2026-08-26/metrics.csv b/results/easycom_loss_structure_4ep_2026-08-26/metrics.csv new file mode 100644 index 0000000..5314659 --- /dev/null +++ b/results/easycom_loss_structure_4ep_2026-08-26/metrics.csv @@ -0,0 +1,31 @@ +loss,seed,horizon_seconds,map,background_ap,camera_wearer_ap,other_people_ap +four-state-ce,0,0.2,73.74955,56.71375,78.57366,85.96124 +four-state-ce,0,0.4,68.82697,49.50218,73.81613,83.16261 +four-state-ce,0,0.6,64.80523,44.45318,69.01941,80.94310 +four-state-ce,0,0.8,61.52546,40.84250,64.65755,79.07634 +four-state-ce,0,1.0,59.44807,39.33581,61.01753,77.99088 +four-state-ce,0,1.2,57.96347,38.34954,58.54043,77.00044 +four-state-ce,0,1.4,56.95413,38.05607,56.56272,76.24359 +four-state-ce,0,1.6,55.84352,37.22674,54.59497,75.70885 +four-state-ce,0,1.8,54.89116,36.51531,52.91825,75.23991 +four-state-ce,0,2.0,54.31858,36.65738,51.36987,74.92851 +independent-bce,0,0.2,73.62153,56.53017,78.40881,85.92561 +independent-bce,0,0.4,68.93990,49.83756,73.84668,83.13544 +independent-bce,0,0.6,64.79984,44.35427,68.98534,81.05992 +independent-bce,0,0.8,61.57880,40.95262,64.40600,79.37779 +independent-bce,0,1.0,59.53538,39.46612,61.35583,77.78420 +independent-bce,0,1.2,57.95764,38.45346,58.30468,77.11479 +independent-bce,0,1.4,56.94317,38.20420,56.46439,76.16092 +independent-bce,0,1.6,56.04943,37.65077,54.86724,75.63029 +independent-bce,0,1.8,55.09841,37.00503,52.91908,75.37111 +independent-bce,0,2.0,54.24044,36.46858,51.18916,75.06359 +lstr-mce,0,0.2,73.44637,56.76438,77.86650,85.70824 +lstr-mce,0,0.4,68.63790,49.90963,73.24394,82.76013 +lstr-mce,0,0.6,64.64750,44.77128,68.47873,80.69249 +lstr-mce,0,0.8,61.50690,41.37775,63.99127,79.15167 +lstr-mce,0,1.0,59.35000,39.43757,61.10979,77.50264 +lstr-mce,0,1.2,58.08335,39.28797,58.19467,76.76740 +lstr-mce,0,1.4,57.22382,39.01062,56.66806,75.99277 +lstr-mce,0,1.6,56.15409,38.03064,54.82056,75.61108 +lstr-mce,0,1.8,55.11616,37.20218,53.15030,74.99598 +lstr-mce,0,2.0,54.32006,37.21908,51.03765,74.70344 diff --git a/results/easycom_loss_structure_4ep_2026-08-26/raw_console.txt b/results/easycom_loss_structure_4ep_2026-08-26/raw_console.txt new file mode 100644 index 0000000..d3bd88d --- /dev/null +++ b/results/easycom_loss_structure_4ep_2026-08-26/raw_console.txt @@ -0,0 +1,59 @@ +Individual runs +run 0.2s mAP BG AP wearer AP others AP mean mAP +four-state-ce_seed0 73.74955 56.71375 78.57366 85.96124 60.83261 +four-state-ce_seed1 73.85667 56.63089 78.86871 86.07041 60.94612 +four-state-ce_seed2 73.82467 56.69228 78.71884 86.06288 60.87591 +independent-bce_seed0 73.62153 56.53017 78.40881 85.92561 60.87646 +independent-bce_seed1 73.79339 56.64809 78.74388 85.98820 60.93730 +independent-bce_seed2 73.70613 56.38458 78.61257 86.12125 60.93824 +lstr-mce_seed0 73.44637 56.76438 77.86650 85.70824 60.84861 +lstr-mce_seed1 73.75696 56.94418 78.57004 85.75664 60.73626 +lstr-mce_seed2 73.91410 57.16263 78.79964 85.78001 60.86305 + +Mean +/- sample standard deviation +loss 0.2s mAP wearer AP others AP mean mAP +lstr-mce 73.70581 +/- 0.23802 78.41206 +/- 0.48622 85.74830 +/- 0.03661 60.81597 +/- 0.06941 +independent-bce 73.70702 +/- 0.08593 78.58842 +/- 0.16884 86.01169 +/- 0.09991 60.91733 +/- 0.03540 +four-state-ce 73.81030 +/- 0.05499 78.72040 +/- 0.14753 86.03151 +/- 0.06097 60.88488 +/- 0.05728 + +loss: four-state-ce +output space: four-state-softmax +0.2s: mAP=73.74955, background=56.71375, wearer=78.57366, others=85.96124 +0.4s: mAP=68.82697, background=49.50218, wearer=73.81613, others=83.16261 +0.6s: mAP=64.80523, background=44.45318, wearer=69.01941, others=80.94310 +0.8s: mAP=61.52546, background=40.84250, wearer=64.65755, others=79.07634 +1.0s: mAP=59.44807, background=39.33581, wearer=61.01753, others=77.99088 +1.2s: mAP=57.96347, background=38.34954, wearer=58.54043, others=77.00044 +1.4s: mAP=56.95413, background=38.05607, wearer=56.56272, others=76.24359 +1.6s: mAP=55.84352, background=37.22674, wearer=54.59497, others=75.70885 +1.8s: mAP=54.89116, background=36.51531, wearer=52.91825, others=75.23991 +2.0s: mAP=54.31858, background=36.65738, wearer=51.36987, others=74.92851 +10-horizon mean mAP: 60.83261 + +loss: independent-bce +output space: three-label-sigmoid +0.2s: mAP=73.62153, background=56.53017, wearer=78.40881, others=85.92561 +0.4s: mAP=68.93990, background=49.83756, wearer=73.84668, others=83.13544 +0.6s: mAP=64.79984, background=44.35427, wearer=68.98534, others=81.05992 +0.8s: mAP=61.57880, background=40.95262, wearer=64.40600, others=79.37779 +1.0s: mAP=59.53538, background=39.46612, wearer=61.35583, others=77.78420 +1.2s: mAP=57.95764, background=38.45346, wearer=58.30468, others=77.11479 +1.4s: mAP=56.94317, background=38.20420, wearer=56.46439, others=76.16092 +1.6s: mAP=56.04943, background=37.65077, wearer=54.86724, others=75.63029 +1.8s: mAP=55.09841, background=37.00503, wearer=52.91908, others=75.37111 +2.0s: mAP=54.24044, background=36.46858, wearer=51.18916, others=75.06359 +10-horizon mean mAP: 60.87646 + +loss: lstr-mce +output space: three-class-softmax +0.2s: mAP=73.44637, background=56.76438, wearer=77.86650, others=85.70824 +0.4s: mAP=68.63790, background=49.90963, wearer=73.24394, others=82.76013 +0.6s: mAP=64.64750, background=44.77128, wearer=68.47873, others=80.69249 +0.8s: mAP=61.50690, background=41.37775, wearer=63.99127, others=79.15167 +1.0s: mAP=59.35000, background=39.43757, wearer=61.10979, others=77.50264 +1.2s: mAP=58.08335, background=39.28797, wearer=58.19467, others=76.76740 +1.4s: mAP=57.22382, background=39.01062, wearer=56.66806, others=75.99277 +1.6s: mAP=56.15409, background=38.03064, wearer=54.82056, others=75.61108 +1.8s: mAP=55.11616, background=37.20218, wearer=53.15030, others=74.99598 +2.0s: mAP=54.32006, background=37.21908, wearer=51.03765, others=74.70344 +10-horizon mean mAP: 60.84861 diff --git a/results/easycom_loss_structure_4ep_2026-08-26/summary.json b/results/easycom_loss_structure_4ep_2026-08-26/summary.json new file mode 100644 index 0000000..cc591a9 --- /dev/null +++ b/results/easycom_loss_structure_4ep_2026-08-26/summary.json @@ -0,0 +1,105 @@ +{ + "schema_version": 1, + "recorded_date": "2026-08-26", + "status": "three_seed_fixed_budget_ablation", + "dataset": "EasyCom", + "split": { + "train_sessions": [4, 5, 6, 7, 8, 9, 10, 11, 12], + "dev_sessions": [], + "test_sessions": [3, 2, 1] + }, + "model": { + "backbone": "Qwen2.5-Omni-3B", + "thinker_frozen": true, + "streaming_mode": "open-stream-replay", + "memory_seconds": 8, + "video_fps": 2, + "prediction_hz": 5, + "selected_layers": "last_4_query_states", + "layer_fusion": "concat-mlp" + }, + "training": { + "epochs": 4, + "batch_size": 512, + "learning_rate": 0.00007, + "weight_decay": 0.00005, + "warmup_epochs": 1.6, + "warmup_factor": 0.3, + "dropout": 0.2, + "seeds": [0, 1, 2], + "checkpoint_selection": "final_epoch_no_dev" + }, + "evaluation": { + "protocol": "causal_valid_only", + "test_sessions": [3, 2, 1], + "horizon_seconds": [0.2, 0.4, 0.6, 0.8, 1.0, 1.2, 1.4, 1.6, 1.8, 2.0] + }, + "three_seed_summary_percent": { + "lstr-mce": { + "horizon_0.2_map": {"mean": 73.70581, "sample_std": 0.23802}, + "horizon_0.2_wearer_ap": {"mean": 78.41206, "sample_std": 0.48622}, + "horizon_0.2_others_ap": {"mean": 85.74830, "sample_std": 0.03661}, + "ten_horizon_mean_map": {"mean": 60.81597, "sample_std": 0.06941} + }, + "independent-bce": { + "horizon_0.2_map": {"mean": 73.70702, "sample_std": 0.08593}, + "horizon_0.2_wearer_ap": {"mean": 78.58842, "sample_std": 0.16884}, + "horizon_0.2_others_ap": {"mean": 86.01169, "sample_std": 0.09991}, + "ten_horizon_mean_map": {"mean": 60.91733, "sample_std": 0.03540} + }, + "four-state-ce": { + "horizon_0.2_map": {"mean": 73.81030, "sample_std": 0.05499}, + "horizon_0.2_wearer_ap": {"mean": 78.72040, "sample_std": 0.14753}, + "horizon_0.2_others_ap": {"mean": 86.03151, "sample_std": 0.06097}, + "ten_horizon_mean_map": {"mean": 60.88488, "sample_std": 0.05728} + } + }, + "individual_run_summary_percent": [ + {"loss": "four-state-ce", "seed": 0, "horizon_0.2_map": 73.74955, "horizon_0.2_background_ap": 56.71375, "horizon_0.2_wearer_ap": 78.57366, "horizon_0.2_others_ap": 85.96124, 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