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Add ConvMemory v3 validity context checkpoint
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[transformers] You passed `num_labels=2` which is incompatible to the `id2label` map of length `3`.
Loading weights: 0%| | 0/202 [00:00<?, ?it/s] Loading weights: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 202/202 [00:00<00:00, 6000.60it/s]
[transformers] DebertaV2ForSequenceClassification LOAD REPORT from: /root/autodl-tmp/hf_models/nli-deberta-v3-base
Key | Status |
------------------+----------+---------------------------------------------------------------------------------------
classifier.weight | MISMATCH | Reinit due to size mismatch - ckpt: torch.Size([3, 768]) vs model:torch.Size([2, 768])
classifier.bias | MISMATCH | Reinit due to size mismatch - ckpt: torch.Size([3]) vs model:torch.Size([2])
Notes:
- MISMATCH: ckpt weights were loaded, but they did not match the original empty weight shapes.
Writing model shards: 0%| | 0/1 [00:00<?, ?it/s] Writing model shards: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 1/1 [00:01<00:00, 1.33s/it] Writing model shards: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 1/1 [00:01<00:00, 1.33s/it]
{
"backbone": "/root/autodl-tmp/hf_models/nli-deberta-v3-base",
"batch_size": 1,
"dev_metrics": {
"demote_recall": 1.0,
"event_all_type_consistency": 1.0,
"fn": 0,
"fp": 0,
"old_target_all_type_consistency": 1.0,
"pair_accuracy": 1.0,
"protect_recall": 1.0,
"target_all_type_consistency": 1.0,
"tn": 1225,
"tp": 175
},
"dev_rows": 1400,
"device": "cuda",
"epochs": 1,
"export": "representative_checkpoint",
"lr": 2e-05,
"margin": 1.0,
"max_length": 192,
"module": "ConvMemory v3 Validity Context Layer",
"notes": [
"The released checkpoint implements the v511 query-conditioned validity method.",
"Multi-seed quality claims should cite the v511/v513/v514 evaluation packets, not this single checkpoint alone.",
"Default mode is context annotation; demotion is explicit opt-in for dense current-state/update workloads."
],
"params": 184423682,
"role_weight": 1.0,
"seed": 7,
"source_config": "results/v514_v3_freeze_config/final_config.json",
"source_method_metrics": "results/v511_memora_retrieval_demotion_benchmark_5seed/REPORT.md",
"source_recipe": "experiments/v511_memora_retrieval_demotion_benchmark.py",
"threshold": 0.5,
"train_frac": 0.8,
"train_rows": 5520,
"train_seconds": 31.500682814978063,
"training_curves": [
{
"ce_loss": 0.27147598006590473,
"epoch": 1,
"role_loss": 0.17152404859223389,
"train_loss": 0.4430000293751895
}
],
"wall_seconds": 39.408347606658936
}