Initial upload: GPUburnout-3B-75K pretrained base (75K steps, val loss 2.2475)

README.md

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+---
+license: apache-2.0
+language:
+  - en
+tags:
+  - llama
+  - pretrained
+  - from-scratch
+  - gpuburnout
+pipeline_tag: text-generation
+---
+
+# GPUburnout-3B-75K
+
+A 3.12 billion parameter Llama-style decoder-only transformer, pretrained from scratch as the Season 4 model in the GPUburnout blog series. Final pretraining checkpoint at 75,000 steps.
+
+This is the base model, before any instruction tuning. For the chat-tuned versions, see [GPUburnout/GPUburnout-3B-75K-Chat](https://huggingface.co/GPUburnout/GPUburnout-3B-75K-Chat) (the shipped SFT champion).
+
+## Model Details
+
+- **Architecture:** Llama-style decoder-only transformer
+- **Parameters:** 3.12B
+- **Hidden size:** 2,560
+- **Intermediate size:** 10,240
+- **Layers:** 32
+- **Attention heads:** 40 query, 10 key/value (GQA)
+- **Head dim:** 64
+- **Vocab size:** 32,005
+- **Max position:** 2,048
+- **Tie word embeddings:** True
+- **Precision:** float16
+
+## Training
+
+- **Steps:** 75,000
+- **Final val loss:** 2.2475
+- **Training cost:** ~$425 (RunPod A100/H200)
+- **Pretraining data mix:** FineWeb-Edu, FineMath, Stack-Edu-Python, PubMed abstracts
+- **Optimizer:** 8-bit AdamW
+- **Hardware:** Mixed A100 SXM 80GB and H200 NVL across training run
+
+## Benchmarks (0-shot, float16)
+
+| Benchmark | Score |
+|---|---|
+| TruthfulQA MC2 | 47.61% |
+| HellaSwag (acc_norm) | 28.30% |
+| ARC-Easy (acc_norm) | 43.06% |
+| ARC-Challenge (acc_norm) | 21.84% |
+| MMLU (5-shot acc) | 23.02% |
+
+These are typical small-model-on-limited-tokens numbers. The model has not seen enough data to develop deep academic knowledge (MMLU is near random). It absorbed enough factual content for ARC-Easy to land ~2x random and for TruthfulQA to score above random on calibrated truthfulness, which is the strongest signal at this scale.
+
+## Related Models
+
+- [GPUburnout/GPUburnout-3B-75K-Chat](https://huggingface.co/GPUburnout/GPUburnout-3B-75K-Chat) - SFT champion (step 1500, lr=5e-5, r=16)
+- [GPUburnout/GPUburnout-3B-75K-Chat-step3000](https://huggingface.co/GPUburnout/GPUburnout-3B-75K-Chat-step3000) - Alternative SFT checkpoint (lowest val loss, not shipped)
+- [GPUburnout/GPUburnout-3B-checkpoints](https://huggingface.co/GPUburnout/GPUburnout-3B-checkpoints) - Intermediate pretraining checkpoints
+
+## Blog
+
+This model is part of the GPUburnout LLM-from-scratch blog series. Season 4 documents the 3B build, including the platform pivot from Thunder to RunPod, MooseFS storage debugging, and the 75K-step pretraining run.
+
+https://gpuburnout.com
+
+## License
+
+Apache 2.0. Free to use, modify, redistribute. Attribution appreciated.

chat_template.jinja

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+{% for message in messages %}<|im_start|>{{ message['role'] }}
+{{ message['content'] }}<|im_end|>
+{% endfor %}{% if add_generation_prompt %}<|im_start|>assistant
+{% endif %}

config.json

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+{
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 1,
+  "dtype": "float16",
+  "eos_token_id": 2,
+  "head_dim": 64,
+  "hidden_act": "silu",
+  "hidden_size": 2560,
+  "initializer_range": 0.02,
+  "intermediate_size": 10240,
+  "max_position_embeddings": 2048,
+  "mlp_bias": false,
+  "model_type": "llama",
+  "num_attention_heads": 40,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 10,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-06,
+  "rope_parameters": {
+    "rope_theta": 500000.0,
+    "rope_type": "default"
+  },
+  "rope_scaling": null,
+  "rope_theta": 10000.0,
+  "tie_word_embeddings": true,
+  "transformers_version": "4.57.6",
+  "use_cache": true,
+  "vocab_size": 32005
+}

generation_config.json

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+{
+  "do_sample": true,
+  "eos_token_id": 32001,
+  "max_new_tokens": 256,
+  "pad_token_id": 1,
+  "repetition_penalty": 1.1,
+  "temperature": 0.7,
+  "top_p": 0.9,
+  "transformers_version": "4.57.6"
+}

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special_tokens_map.json

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+{
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tokenizer_config.json

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