| { |
| "data": { |
| "dev": "/content/jevlet_data/mixture_v6/dev.jsonl", |
| "train": "/content/jevlet_data/mixture_v6/train.jsonl", |
| "vault": "/content/jevlet_data/mixture_v6/vault/vault.jsonl" |
| }, |
| "device": "auto", |
| "evaluation": { |
| "batch_size": 64, |
| "benchmark_repeats": 5, |
| "max_examples": 6000, |
| "permutation_examples": 64 |
| }, |
| "model": { |
| "attention_topology": "block_bidir", |
| "backbone": "BAAI/bge-small-en-v1.5", |
| "decision_head": "pointer", |
| "family": "pretrained", |
| "gradient_checkpointing": false, |
| "max_option_tokens": 40, |
| "max_packed_len": 1024, |
| "max_question_tokens": 64, |
| "max_state_tokens": 224, |
| "option_pool": "mean" |
| }, |
| "notes": "Same 1.6M-example budget as pretrained_daily_v6.json (100k x 16) at effective batch 64: 25k steps, learning rates scaled by sqrt(4), warmup and snapshots at the same example counts. jevlet.colab fits batch_size x gradient_accumulation to the GPU and keeps their product at effective_batch.", |
| "provenance": { |
| "base_config": "configs/pretrained_daily_v6_colab.json", |
| "created": 1790338776.0874045, |
| "git_commit": "9d62c46989e965e0d823491e670dc01ed12a345e" |
| }, |
| "seed": 1337, |
| "sessions": [ |
| { |
| "gpu": { |
| "batch_size": 64, |
| "bf16": true, |
| "memory_gb": 79.3, |
| "name": "NVIDIA A100-SXM4-80GB", |
| "workers": 8 |
| }, |
| "resume": false, |
| "time": 1790338782.2884605 |
| }, |
| { |
| "gpu": { |
| "batch_size": 64, |
| "bf16": true, |
| "memory_gb": 79.3, |
| "name": "NVIDIA A100-SXM4-80GB", |
| "workers": 8 |
| }, |
| "resume": true, |
| "time": 1790352643.7766407 |
| } |
| ], |
| "training": { |
| "amp_dtype": "bf16", |
| "backbone_learning_rate": 0.0001, |
| "batch_size": 64, |
| "effective_batch": 64, |
| "gradient_accumulation": 1, |
| "keep_steps": [ |
| 2500, |
| 6250, |
| 12500 |
| ], |
| "learning_rate": 0.002, |
| "log_every_steps": 50, |
| "loss": "ce_brier", |
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| "max_steps": 25000, |
| "min_lr_ratio": 0.05, |
| "mirror_dir": "/content/drive/MyDrive/Jevlet/runs/v6", |
| "num_workers": 8, |
| "resume_from": "/content/runs/v6/resume.pt", |
| "save_every_steps": 500, |
| "warmup_steps": 500, |
| "weight_decay": 0.01 |
| } |
| } |
|
|
