Thyme: Think Beyond Images
Paper • 2508.11630 • Published • 81
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Check out the documentation for more information.
Thyme SFT checkpoints from reproducing Table 5 "+Only Last Round" of Thyme paper.
See full repro notes at Irisicy4/Thyme-projects @ refactor-reproduce-notes.
| Folder | Config | Train epochs | train_loss | Notes |
|---|---|---|---|---|
SFT-baseline-bs128-seed42/checkpoint-4251 |
effective batch 128 (matches paper) | 3 | 0.274 | main result |
SFT-baseline-bs64-DEPRECATED-seed42/checkpoint-8499 |
effective batch 64 (half-paper, setup error) | 3 | 0.206 | partially eval'd |
SFT-baseline-bs64-partial-seed42/checkpoint-1500 |
bs64 — partial | 0.5 | n/a | killed mid-training |
SFT-no123-bs64-partial-seed42/checkpoint-2000 |
bs64 — partial — no123 ablation | 0.7 | n/a | killed mid-training |
All checkpoints are fine-tunes of Qwen/Qwen2.5-VL-7B-Instruct. Load with:
from transformers import AutoModelForCausalLM, AutoProcessor
mp = "Icey444/ttthyme-ckpts/SFT-baseline-bs128-seed42/checkpoint-4251"
model = AutoModelForCausalLM.from_pretrained(mp, trust_remote_code=True)
processor = AutoProcessor.from_pretrained(mp)
Or with VLMEvalKit + the Thyme code-execution sandbox loop (see repro notes §13 in the Irisicy4 repo branch above).