Model details
- Model name:
A.X-3.1-Light SFT Source Screen 71875 (Essential Medical 3K)
- Base model:
skt/A.X-3.1-Light
- Base model revision:
9b41bb2406472634d8812c0b8931fa40fa9a6c3a
- Fine-tuning: LoRA supervised fine-tuning, merged into base weights
- Weight format: BF16
safetensors
- Architecture: unchanged Llama causal language model architecture
- Chat template: bundled A.X tokenizer chat template
- Custom model code: none; standard Transformers/vLLM loading is intended
Training data
Training used only AI Hub dataset 71875, 필수의료 의학지식 데이터. The
training split contains 3,000 selected examples and the separate development
split contains 300 examples. No v0.21 mixture, other AI Hub dataset, public
benchmark question, benchmark answer, or evaluation artifact was used as SFT
data or included in this repository.
Table with columns: Source, Training examples| Source | Training examples |
|---|
| Category 14 | 895 |
| Category 15 | 895 |
| Category 16 | 315 |
| Category 17 | 895 |
| Total | 3,000 |
The output contract is answer-first (정답: ...). Depending on the source
question, the target is a label, number, short answer, or concise explanation.
Examples over 2,048 chat-template tokens were excluded rather than truncated;
the training summary reports zero runtime truncation. The applicable AI Hub
terms of use remain in force. AI Hub dataset 71875
Training configuration
- Epochs: 1
- Optimizer steps: 375
- Maximum sequence length: 2,048
- Precision: BF16
- Per-device batch size: 1
- Gradient accumulation: 8 (effective batch size 8)
- Learning rate:
5e-5
- Scheduler: cosine; warmup ratio
0.03 (11 steps)
- Weight decay:
0.01
- Random seed: 42
- LoRA rank / alpha / dropout: 16 / 32 / 0.05
- LoRA target modules:
q_proj, k_proj, v_proj, , , ,
Usage
from transformers import AutoModelForCausalLM, AutoTokenizer
model_id = "youngseok12/AX-3.1-Light-sft_source_screen_71875_3000"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(
model_id,
torch_dtype="auto",
device_map="auto",
)
Use the bundled tokenizer chat template for conversational inference. The
repository is a merged full model and does not require PEFT adapter loading.
Limitations and license
This model is derived from the Apache-2.0 licensed skt/A.X-3.1-Light model;
the base model notices and SK Telecom trademark terms also apply. AI Hub terms
apply to the source dataset. See LICENSE and the base model
repository for the applicable terms.
The model can produce incorrect, incomplete, biased, or poorly formatted
answers. It has not been validated as a medical device or professional medical
advice system and must not be used as the sole basis for clinical decisions.