modrill
qwen3-4b-nothink-s1-full-sft
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README
License: apache-2.0Model description
- Method: full SFT (all weights trainable), DeepSpeed ZeRO-2, 4 GPUs
- Dataset: oci_nothink_50k (50,000 examples)
- Template: qwen3_nothink
- Not LoRA / not QLoRA: entire 4B model was updated
Note: The final training save was interrupted by disk full; published weights were restored from checkpoint-782 (same step count as training completion).
Training details
| Field | Value |
|---|---|
| Epochs | 1 |
| Seed | 42 |
| cutoff_len | 4096 |
| packing | false |
| per_device_train_batch_size | 4 |
| gradient_accumulation_steps | 4 |
| effective_batch_size | 64 (4 x 4 x 4 GPUs) |
| learning_rate | 3e-5 |
| train_loss | 0.1572 |
| train_steps | 782 |
| finished_at | 2026-06-10 06:18 CST |
| runtime | ~53 min |
Related models
- Think SFT (same project): modrill/qwen3-4b-think-s1-ep23-full-sft - ocr_think_50k, qwen3 template
- Base: Qwen/Qwen3-4B-Base
Usage
python
from transformers import AutoModelForCausalLM, AutoTokenizerrepo_id = "modrill/qwen3-4b-nothink-s1-full-sft"tokenizer = AutoTokenizer.from_pretrained(repo_id, trust_remote_code=True)model = AutoModelForCausalLM.from_pretrained(repo_id,torch_dtype="auto",device_map="auto",trust_remote_code=True,)
License
Released under Apache 2.0 (see upstream Qwen model card if not bundled here).
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