modrill
qwen3-4b-nothink-baseline-full-sft
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README
License: apache-2.0Training summary
| Field | Value |
|---|---|
| Method | Full SFT (ZeRO-2) |
| Dataset | nothink_mix |
| Chat template | qwen3_nothink |
| Epochs | 2 |
| Seed | 42 |
| Cutoff length | 8192 |
| Packing | false |
| Per-device batch size | 4 |
| Gradient accumulation | 4 |
| Effective batch size | 64 |
| Learning rate | 2e-5 |
| Train loss | 0.1898 |
| Train steps | 2988 |
| Finished | 2026-06-08 07:10 CST |
Usage
Load with Hugging Face Transformers:
python
from transformers import AutoModelForCausalLM, AutoTokenizermodel_id = "modrill/qwen3-4b-nothink-baseline-full-sft"tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)
Training hyperparameters
- learning_rate: 2e-05
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU (4 devices)
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: AdamW (fused)
- lr_scheduler: cosine
- lr_scheduler_warmup_steps: 0.03
- num_epochs: 2.0
Framework versions
- Transformers 5.6.0
- PyTorch 2.8.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2
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