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jiosephlee
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Model Details
Model Provider
jiosephlee
Model Tree
jiosephlee/Intern-S1-mini-lm
Input Modalities
Output Modalities
Supported Functionality
jiosephlee/Intern-S1-mini-lm (Qwen3ForCausalLM, vocab 153216)jiosephlee/assay-transfer-intern (158,429 train rows)paged_adamw_8bit(A) / (B)This checkpoint is the best-validation snapshot (step 50), promoted by the assay-transfer callback on binary macro-F1.
| Metric | Value |
|---|---|
| Binary macro-F1 | 0.6612 |
| Binary accuracy | 0.7046 |
| Parse rate | 1.00 |
| assay_concept group-avg macro-F1 | 0.6321 |
| tanimoto_bucket group-avg macro-F1 | 0.6316 |
Per-assay macro-F1: Fa 0.532, Fg 0.593, Fh 0.704, oral_bioavailability 0.600, oral_exposure 0.732. Per-Tanimoto-bucket macro-F1: high 0.664, low 0.600.
python
from transformers import AutoModelForCausalLM, AutoTokenizertok = AutoTokenizer.from_pretrained("jiosephlee/assay-transfer-tool", trust_remote_code=True)model = AutoModelForCausalLM.from_pretrained("jiosephlee/assay-transfer-tool", torch_dtype="bfloat16")