78 lines
2.3 KiB
Markdown
78 lines
2.3 KiB
Markdown
---
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license: apache-2.0
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language:
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- en
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tags:
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- llama
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- pretrained
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- from-scratch
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- gpuburnout
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- chinchilla-optimal
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pipeline_tag: text-generation
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---
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# GPUburnout-1B-160K
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A 1.04 billion parameter Llama-style language model trained from scratch to Chinchilla-optimal on 20.97B tokens.
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This is the **160K step (Chinchilla-optimal)** checkpoint. For the earlier 90K step checkpoint, see [GPUburnout-1B](https://huggingface.co/GPUburnout/GPUburnout-1B).
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## Model Details
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- **Architecture:** Llama-style decoder-only transformer
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- **Parameters:** 1.04B
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- **Hidden dim:** 2048
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- **Layers:** 16
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- **Attention:** GQA (32 query heads, 8 KV heads)
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- **FFN:** SwiGLU (intermediate 8192)
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- **Position encoding:** RoPE (theta=500000)
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- **Context length:** 2048 tokens
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- **Vocabulary:** 32,005 tokens (BPE + 5 special tokens)
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- **Weight tying:** Yes (embedding + LM head)
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## Training
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- **Data:** 20.97B tokens (FineWeb-Edu 85%, Python-Edu 4.2%, FineMath 10.8%)
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- **Hardware:** A100 SXM 80GB on RunPod
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- **Steps:** 160,000 (Chinchilla-optimal: 20x params in tokens)
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- **Final loss:** 2.446
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- **Throughput:** ~30,500 tokens/sec
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### Training Phases
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| Phase | Steps | Loss | Cost |
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|---|---|---|---|
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| Phase 1 (smoke test) | 200 | ~6-7 | ~$0.50 |
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| Phase 2 (proof of life) | 10K | 2.93 | ~$22 |
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| Phase 3 | 60K | 2.57 | ~$94 |
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| Phase 4 | 90K | 2.494 | ~$61 |
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| Phase 5 (spot) | 120K | 2.530 | ~$34 |
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| Phase 6 (spot, Chinchilla) | 160K | 2.446 | — |
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## Tokenizer
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Includes ChatML special tokens for SFT:
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- `<|im_start|>` (32000), `<|im_end|>` (32001)
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- `<|system|>` (32002), `<|user|>` (32003), `<|assistant|>` (32004)
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## Usage
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model = AutoModelForCausalLM.from_pretrained("GPUburnout/GPUburnout-1B-160K", torch_dtype="float16")
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tokenizer = AutoTokenizer.from_pretrained("GPUburnout/GPUburnout-1B-160K")
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inputs = tokenizer("The capital of France is", return_tensors="pt")
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outputs = model.generate(**inputs, max_new_tokens=50)
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print(tokenizer.decode(outputs[0], skip_special_tokens=True))
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```
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## Blog
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Full training journey documented at [gpuburnout.com](https://gpuburnout.com)
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## Author
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Jun Park ([@GPUburnout](https://github.com/GPUburnout))
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