49 lines
1.3 KiB
Markdown
49 lines
1.3 KiB
Markdown
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---
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language:
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- en
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license: apache-2.0
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base_model: Qwen/Qwen2.5-7B-Instruct
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library_name: transformers
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pipeline_tag: text-generation
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tags:
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- logical-reasoning
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- sft
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- qwen2.5
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---
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# Qwen2.5-7B-Instruct — ProofDAG SFT
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Full fine-tune của **Qwen/Qwen2.5-7B-Instruct** trên dataset ProofDAG (True / False / Uncertain).
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## Training
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|---|---|
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| Data | 5640 train / 330 val (multi-turn chat) |
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| Hardware | 8× L40 (FSDP FULL_SHARD, bf16) |
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| Global batch | 128, max_len 4096 |
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| LR | 1e-6 cosine, warmup 0.03 |
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| Epochs | 3 (132 steps, 6h 48m) |
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| Final train / eval loss | 0.207 / 0.251 |
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## Quick start
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```python
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from transformers import AutoTokenizer, AutoModelForCausalLM
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mid = "NhatCuong22/qwen2.5-7b-proofdag-sft"
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tok = AutoTokenizer.from_pretrained(mid)
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model = AutoModelForCausalLM.from_pretrained(mid, torch_dtype="bfloat16", device_map="auto")
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messages = [
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{"role": "system", "content": "You are a helpful AI assistant."},
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{"role": "user", "content": "Premises:\n1. If it rains, the ground is wet.\n2. It rains.\n\nProposed conclusion: The ground is wet."},
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]
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prompt = tok.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
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out = model.generate(**tok(prompt, return_tensors="pt").to(model.device), max_new_tokens=512)
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print(tok.decode(out[0], skip_special_tokens=True))
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```
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License: Apache-2.0
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