TopG: models, corpora and frozen evaluation sets
Browse files- G_1000/arm_meta.json +77 -0
- G_1000/ckpt_00020.pt +3 -0
- G_1000/ckpt_00100.pt +3 -0
- G_1000/final_mpw_ep00020.json +0 -0
- G_1000/final_mpw_ep00100.json +0 -0
- G_1000/final_strat_ep00020.json +0 -0
- G_1000/final_strat_ep00100.json +0 -0
- G_1000/history.json +705 -0
- G_1001/arm_meta.json +77 -0
- G_1001/ckpt_00020.pt +3 -0
- G_1001/ckpt_00100.pt +3 -0
- G_1001/final_mpw_ep00020.json +0 -0
- G_1001/final_mpw_ep00100.json +0 -0
- G_1001/final_strat_ep00020.json +0 -0
- G_1001/final_strat_ep00100.json +0 -0
- G_1001/history.json +705 -0
- G_1002/arm_meta.json +77 -0
- G_1002/ckpt_00020.pt +3 -0
- G_1002/ckpt_00100.pt +3 -0
- G_1002/final_mpw_ep00020.json +0 -0
- G_1002/final_mpw_ep00100.json +0 -0
- G_1002/final_strat_ep00020.json +0 -0
- G_1002/final_strat_ep00100.json +0 -0
- G_1002/history.json +705 -0
- H_pq0/arm_meta.json +85 -0
- H_pq0/ckpt_00020.pt +3 -0
- H_pq0/ckpt_00100.pt +3 -0
- H_pq0/depth2.json +0 -0
- H_pq0/depth3.json +0 -0
- H_pq0/depth4.json +0 -0
- H_pq0/depth6.json +0 -0
- H_pq0/history.json +705 -0
- H_pq1/arm_meta.json +85 -0
- H_pq1/ckpt_00020.pt +3 -0
- H_pq1/ckpt_00100.pt +3 -0
- H_pq1/depth2.json +0 -0
- H_pq1/depth3.json +0 -0
- H_pq1/depth4.json +0 -0
- H_pq1/depth6.json +0 -0
- H_pq1/history.json +705 -0
- H_pq2/arm_meta.json +85 -0
- H_pq2/ckpt_00020.pt +3 -0
- H_pq2/ckpt_00100.pt +3 -0
- H_pq2/depth2.json +0 -0
- H_pq2/depth3.json +0 -0
- H_pq2/depth4.json +0 -0
- H_pq2/depth6.json +0 -0
- H_pq2/history.json +705 -0
- README.md +84 -0
- SHA256SUMS.json +24 -0
G_1000/arm_meta.json
ADDED
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{
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| 2 |
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"arm": "G_1000",
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| 3 |
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"seed": 0,
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| 4 |
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"seed_witness": "f2e603df160ea17e",
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| 5 |
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"seeded_rngs": [
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"random",
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"numpy",
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| 8 |
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"torch"
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| 9 |
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],
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| 10 |
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"corpus": {
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| 11 |
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"path": "data/v2/s2/train_stage1.json",
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| 12 |
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"content_hash": "93739a93f8f629e63b5758debf15b894a2c8934aad73e8074181fec97eac3075",
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| 13 |
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"n_records": 69190,
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| 14 |
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"n_encodable": 69190,
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| 15 |
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"generator": "v2.run_phase_d.split",
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| 16 |
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"params": {
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| 17 |
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"key": "skeleton",
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| 18 |
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"val_fraction": 0.2,
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| 19 |
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"seed": 0,
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| 20 |
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"source_corpus": "data/v2/corpus_stage2.json",
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"corpus_hash": "6e111bdcd852016362b4f25e27d192d1d286421d4f600ccf5b9bbb14506bda6c"
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| 22 |
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}
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| 23 |
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},
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| 24 |
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"encode_drops": {
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| 25 |
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"stage": "dataset:encode",
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| 26 |
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"n_input": 69190,
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| 27 |
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"n_kept": 69190,
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| 28 |
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"dropped": {}
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| 29 |
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},
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| 30 |
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"split": {
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| 31 |
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"key": "skeleton",
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| 32 |
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"seed": 0,
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| 33 |
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"val_fraction": 0.1,
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| 34 |
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"counts": {
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| 35 |
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"train": 62313,
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| 36 |
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"val": 6877
|
| 37 |
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},
|
| 38 |
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"hashes": {
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| 39 |
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"train": "23f199f139ae69626162a7e60af566a297f1a269994bcfdcb0627e6e3cb7f7ab",
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| 40 |
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"val": "712197b0032eef37514ba71a9af726ef96ed00a25b4360a670087e8236c60f65"
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| 41 |
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},
|
| 42 |
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"key_counts": {
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| 43 |
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"train": 21957,
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| 44 |
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"val": 2440
|
| 45 |
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}
|
| 46 |
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},
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| 47 |
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"model": {
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| 48 |
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"vocab_size": 2317,
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| 49 |
+
"d_model": 256,
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| 50 |
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"n_layers": 4,
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| 51 |
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"n_heads": 8,
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| 52 |
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"d_ff": 1024,
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| 53 |
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"dropout": 0.1,
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| 54 |
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"max_seq": 102,
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| 55 |
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"version": "v2-model-1",
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| 56 |
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"pipeline_version": "v2.0.0"
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| 57 |
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},
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| 58 |
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"vocab_hash": "3e2eb3f5475497a1ea8754b925e1164d46cbaf5887fa6dd3dcaf78ae9b21e5f3",
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| 59 |
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"tokenizer_version": "v2-tok-3",
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| 60 |
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"dataset_version": "v2-data-1",
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| 61 |
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"pipeline_version": "v2.0.0",
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| 62 |
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"git_commit": "92904f66ea256950c2bbb195eb60ffa818910114",
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| 63 |
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"hyper": {
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| 64 |
+
"epochs": 100,
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| 65 |
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"batch": 128,
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| 66 |
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"lr": 0.0003,
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| 67 |
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"val_fraction": 0.1,
|
| 68 |
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"split_seed": 0
|
| 69 |
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},
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| 70 |
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"code_hash": "5fc4b21b97f3bf87f76802b958080d2f77fb3a1728af86bc1f1f5a9ef582fff9",
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| 71 |
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"device": "cuda",
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| 72 |
+
"started_utc": "2026-08-08T00:05:51Z",
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| 73 |
+
"train_seconds": 5906.0,
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| 74 |
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"final_val_loss": 3.00714,
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| 75 |
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"final_train_loss": 2.25972,
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| 76 |
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"complete": true
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| 77 |
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}
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G_1000/ckpt_00020.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:4359325fd8d74a9c3def65df5bd57ffdd8d83d0e7c8b97866d2339e870794487
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size 18074210
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G_1000/ckpt_00100.pt
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version https://git-lfs.github.com/spec/v1
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| 2 |
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oid sha256:c7676346cc2f72e5696e1a84d4c38c362f5a8fe8b806f91e39db3c6a8e9fc8a1
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size 18074210
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G_1000/final_mpw_ep00020.json
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The diff for this file is too large to render.
See raw diff
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G_1000/final_mpw_ep00100.json
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The diff for this file is too large to render.
See raw diff
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G_1000/final_strat_ep00020.json
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The diff for this file is too large to render.
See raw diff
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G_1000/final_strat_ep00100.json
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The diff for this file is too large to render.
See raw diff
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G_1000/history.json
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@@ -0,0 +1,705 @@
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|
G_1001/arm_meta.json
ADDED
|
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|
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|
G_1001/ckpt_00020.pt
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G_1001/final_mpw_ep00100.json
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G_1001/final_strat_ep00020.json
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G_1001/history.json
ADDED
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@@ -0,0 +1,705 @@
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G_1002/arm_meta.json
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G_1002/ckpt_00020.pt
ADDED
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version https://git-lfs.github.com/spec/v1
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oid sha256:c50ac0288490f96c6ee4f91777d8d3e3a82773c3c04a7de4edf5a7207b9bed6b
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size 18074210
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G_1002/ckpt_00100.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:9bb0b3e51bdf8f79a113cd6da70f6130debf66d26cf9e4e0df740e3d59876af5
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size 18074210
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G_1002/final_mpw_ep00020.json
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G_1002/final_mpw_ep00100.json
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G_1002/final_strat_ep00020.json
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G_1002/final_strat_ep00100.json
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G_1002/history.json
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H_pq0/arm_meta.json
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H_pq0/ckpt_00020.pt
ADDED
|
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H_pq0/ckpt_00100.pt
ADDED
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H_pq0/depth2.json
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H_pq0/depth3.json
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H_pq0/depth4.json
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H_pq0/depth6.json
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H_pq0/history.json
ADDED
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H_pq1/arm_meta.json
ADDED
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@@ -0,0 +1,85 @@
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|
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|
H_pq1/ckpt_00020.pt
ADDED
|
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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size 18080482
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H_pq1/ckpt_00100.pt
ADDED
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@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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H_pq1/depth2.json
ADDED
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H_pq1/depth3.json
ADDED
|
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|
H_pq1/depth4.json
ADDED
|
The diff for this file is too large to render.
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H_pq1/depth6.json
ADDED
|
The diff for this file is too large to render.
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|
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H_pq1/history.json
ADDED
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@@ -0,0 +1,705 @@
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|
| 661 |
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
| 704 |
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|
| 705 |
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|
H_pq2/arm_meta.json
ADDED
|
@@ -0,0 +1,85 @@
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|
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|
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|
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|
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|
|
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|
|
|
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|
|
|
|
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|
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|
|
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|
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|
|
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|
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|
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|
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|
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|
|
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|
|
|
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|
|
|
|
|
|
|
|
|
|
|
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|
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|
|
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|
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|
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|
| 1 |
+
{
|
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"arm": "H_pq2",
|
| 3 |
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|
| 4 |
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"seed_witness": "f2a8e585693907e0",
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| 5 |
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| 8 |
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|
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| 10 |
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"key": "skeleton",
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| 18 |
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"val_fraction": 0.2,
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|
| 25 |
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"stage": "dataset:encode",
|
| 26 |
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|
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| 28 |
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|
| 29 |
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| 30 |
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"split": {
|
| 31 |
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|
| 32 |
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|
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|
| 34 |
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| 47 |
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| 48 |
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|
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|
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|
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|
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|
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|
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"hyper": {
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| 65 |
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|
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"lr": 0.0003,
|
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|
| 68 |
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| 69 |
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|
| 70 |
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"depth_distribution": {
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| 71 |
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|
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|
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|
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|
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|
| 79 |
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"device": "cuda",
|
| 80 |
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"started_utc": "2026-08-08T17:01:12Z",
|
| 81 |
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|
| 82 |
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|
| 83 |
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|
| 84 |
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"complete": true
|
| 85 |
+
}
|
H_pq2/ckpt_00020.pt
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
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oid sha256:93da32c85495eaa97e7812764b4dbd24f869a86acf5d3cd8b2c541d8aaff7351
|
| 3 |
+
size 18080482
|
H_pq2/ckpt_00100.pt
ADDED
|
@@ -0,0 +1,3 @@
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+
version https://git-lfs.github.com/spec/v1
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size 18080482
|
H_pq2/depth2.json
ADDED
|
The diff for this file is too large to render.
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|
H_pq2/depth3.json
ADDED
|
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See raw diff
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|
H_pq2/depth4.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
H_pq2/depth6.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
H_pq2/history.json
ADDED
|
@@ -0,0 +1,705 @@
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|
| 705 |
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}
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| 1 |
+
---
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| 2 |
+
license: mit
|
| 3 |
+
tags: [crystal-structure-prediction, materials-science, transformer, coordination-chemistry]
|
| 4 |
+
library_name: pytorch
|
| 5 |
+
---
|
| 6 |
+
|
| 7 |
+
# TopG — a coordination-conditioned generator of periodic cation frameworks
|
| 8 |
+
|
| 9 |
+
**Status: research artifact, mid-project. Read the limitations before using any number.**
|
| 10 |
+
|
| 11 |
+
Given a *coordination query* — for each inequivalent metal site, its site symmetry, coordination
|
| 12 |
+
sequence and shell-distance ratios — the model emits a **complete crystal structure**: space group,
|
| 13 |
+
Wyckoff positions, free coordinates and free cell-shape parameters. Nothing downstream re-derives
|
| 14 |
+
any of it.
|
| 15 |
+
|
| 16 |
+
## Model
|
| 17 |
+
|
| 18 |
+
| | |
|
| 19 |
+
|---|---|
|
| 20 |
+
| architecture | causal transformer decoder, 4 layers, d=256, 8 heads, FFN 1024 |
|
| 21 |
+
| parameters | **4.5 M** |
|
| 22 |
+
| conditioning | one prefix token per site + one global token (so k is a sequence length, not a weight shape) |
|
| 23 |
+
| vocabulary | 2,317 tokens — per-space-group Wyckoff labels, coarse/fine coordinate and cell grids |
|
| 24 |
+
| training | 69,190 enumerated records, 100 epochs, ~100 min on a Quadro RTX 4000 |
|
| 25 |
+
|
| 26 |
+
Two families, three seeds each:
|
| 27 |
+
- **`G_100*`** — full-depth queries (all six shells specified).
|
| 28 |
+
- **`H_pq*`** — partial queries: trained with the query depth truncated to 2–6 shells from a declared,
|
| 29 |
+
seeded distribution, so a user can ask for less than six shells.
|
| 30 |
+
|
| 31 |
+
Two checkpoints per arm, because **the two halves of the task peak at different times**:
|
| 32 |
+
- `ckpt_00020.pt` — best validation loss, best **skeleton** accuracy.
|
| 33 |
+
- `ckpt_00100.pt` — best **geometry** (r3). Measured, paired, 3 seeds: r3 1.50%→2.50% (p=0.017) and
|
| 34 |
+
1.02%→2.86% (p=0.0005) between these two points, while skeleton-exact falls.
|
| 35 |
+
|
| 36 |
+
**There is no single best checkpoint. Select per metric and say which you used.**
|
| 37 |
+
|
| 38 |
+
## What it does well
|
| 39 |
+
|
| 40 |
+
| capability | measured [per-QUERY unless stated] |
|
| 41 |
+
|---|---|
|
| 42 |
+
| emits a valid parseable structure | **99%** of beams; every death diagnosed as a model choice |
|
| 43 |
+
| predicts N without being told | **92% per candidate**, 98.75% per query |
|
| 44 |
+
| predicts k without being told | **97% per candidate** |
|
| 45 |
+
| names the exact skeleton (sg + Wyckoff labels + N) | **58.8%** |
|
| 46 |
+
| satisfies a **2-shell** query (r0) | **61.5%** |
|
| 47 |
+
|
| 48 |
+
Skeleton accuracy is roughly flat from N=2 to N=192 and k=2 to k=11.
|
| 49 |
+
|
| 50 |
+
## What it does not do
|
| 51 |
+
|
| 52 |
+
**Metric precision.** r3 (six shells + 4% distance tolerance — the project's historical criterion) is
|
| 53 |
+
**2.5–3.1%**. Loosening the tolerance to 15% reaches only ~5.5%: the distances are wrong, not nearly
|
| 54 |
+
right. Structure:
|
| 55 |
+
|
| 56 |
+
- **Below ndim ≈ 9 the CELL is the binding constraint.** In cubic, where symmetry fixes the cell
|
| 57 |
+
entirely, r3 is **18.75% vs 0.25%** — matched on N and k, and on ndim.
|
| 58 |
+
- **Above ndim ≈ 9 the COORDINATES bind.** Cubic scores zero there too.
|
| 59 |
+
- Every r3 success in the evaluation sits at **ndim ≤ 9 and k ≤ 4**.
|
| 60 |
+
|
| 61 |
+
## Honest instrument facts
|
| 62 |
+
|
| 63 |
+
- **Grid ceiling 95.67%** — a *perfect* model scores 95.67%, not 100%, on this evaluation set at this
|
| 64 |
+
emission grid. Ground truth round-tripped through encode→decode→rebuild.
|
| 65 |
+
- **Model-free control: 0/400.** Oracle skeleton + the training split's median geometry scores zero.
|
| 66 |
+
- **Train-seed noise floor: 2–4 pp** on skeleton, **0.5 pp** on r3, from 3 cold starts differing only
|
| 67 |
+
in the seed. **No discrete claim below ~9 pp is interpretable from a single run at a long epoch
|
| 68 |
+
budget.**
|
| 69 |
+
|
| 70 |
+
## Limitations
|
| 71 |
+
|
| 72 |
+
- Trained on **enumerated (synthetic) structures only**. Materials Project data is held out for
|
| 73 |
+
evaluation and never trained on (enforced in code).
|
| 74 |
+
- Space groups 3–230; **triclinic is thin** (348 corpus records) and cubic external validation is
|
| 75 |
+
effectively absent (7 MP queries survive rebuild).
|
| 76 |
+
- Queries are **scale-free** — the model emits cell *shape*, never absolute length.
|
| 77 |
+
- No refinement step exists yet, so the "model output as a starting point" question is open.
|
| 78 |
+
|
| 79 |
+
## Provenance
|
| 80 |
+
|
| 81 |
+
Code, every preregistration, every result and every correction:
|
| 82 |
+
**https://github.com/rgpalgrave/TopG**. `SHA256SUMS.json` here matches the checkpoints; each
|
| 83 |
+
`arm_meta.json` records the corpus hash, split hashes, seed, vocab hash, tokenizer version and git
|
| 84 |
+
commit.
|
SHA256SUMS.json
ADDED
|
@@ -0,0 +1,24 @@
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|
|
| 1 |
+
{
|
| 2 |
+
"models": {
|
| 3 |
+
"G_1000/ckpt_00020.pt": "4359325fd8d74a9c3def65df5bd57ffdd8d83d0e7c8b97866d2339e870794487",
|
| 4 |
+
"G_1000/ckpt_00100.pt": "c7676346cc2f72e5696e1a84d4c38c362f5a8fe8b806f91e39db3c6a8e9fc8a1",
|
| 5 |
+
"G_1001/ckpt_00020.pt": "239f1ec867f729d37a2bbc6dd2883ac5d0780e9d1f2484ec99d1dc52d79a408d",
|
| 6 |
+
"G_1001/ckpt_00100.pt": "435fc46147362762731c79af033b86ec79b8f5a1217a648a9d6e9a64842bb021",
|
| 7 |
+
"G_1002/ckpt_00020.pt": "c50ac0288490f96c6ee4f91777d8d3e3a82773c3c04a7de4edf5a7207b9bed6b",
|
| 8 |
+
"G_1002/ckpt_00100.pt": "9bb0b3e51bdf8f79a113cd6da70f6130debf66d26cf9e4e0df740e3d59876af5",
|
| 9 |
+
"H_pq0/ckpt_00020.pt": "75bdfa1193ced1da08004b1f068f1081f836a541c273152c964478b62eb780d2",
|
| 10 |
+
"H_pq0/ckpt_00100.pt": "f8457297646ba3d9c997579b7683ec1c421f9b5ade1f6114df820a6911abce9f",
|
| 11 |
+
"H_pq1/ckpt_00020.pt": "ccffa3de74cbe87aed963bcfcec41d3547cab5d46d811e7811850ec250eaf840",
|
| 12 |
+
"H_pq1/ckpt_00100.pt": "716c2ea5954be2c5c401fbfe6273bb7393a5322b3b56fca3be7f340cbd13faf5",
|
| 13 |
+
"H_pq2/ckpt_00020.pt": "93da32c85495eaa97e7812764b4dbd24f869a86acf5d3cd8b2c541d8aaff7351",
|
| 14 |
+
"H_pq2/ckpt_00100.pt": "e0451240f5cbba903b87ce87c658a069928687d24b5e121092afc4d49fe99334"
|
| 15 |
+
},
|
| 16 |
+
"datasets": {
|
| 17 |
+
"eval_frozen_stage1.json": "6ed231577de13b4261e6fff18d3a1bda2c6091e8c632844e1665379e885f7210",
|
| 18 |
+
"eval_frozen_mpweighted.json": "1b279af9b7b7f3caa1b456c7f41b53fbed0f4c9fbec18b56230831fbe6292c4e",
|
| 19 |
+
"mp_eval_population_allsystems.json": "014c1988996b3476a1083f9f259d8956ee458de3de63c67f0cd1634bd32eaad3",
|
| 20 |
+
"phase_d_summary.json": "2727a0024858f9a8c0cafd81948209e66bae3b55ef9f56f916192702d22a8d8f",
|
| 21 |
+
"corpus_stage2.json": "6e111bdcd852016362b4f25e27d192d1d286421d4f600ccf5b9bbb14506bda6c",
|
| 22 |
+
"train_stage1.json": "93739a93f8f629e63b5758debf15b894a2c8934aad73e8074181fec97eac3075"
|
| 23 |
+
}
|
| 24 |
+
}
|