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llama2-7b-coding-fft

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Upload FFT model trained on coding datasets

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  1. README.md +87 -0
  2. config.json +28 -0
  3. generation_config.json +10 -0
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README.md ADDED
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+ ---
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+ language:
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+ - en
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+ license: llama2
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+ tags:
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+ - code
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+ - llama2
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+ - full-fine-tuning
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+ - mask-fine-tuning
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+ - coding
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+ datasets:
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+ - tulu3_persona_python
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+ - evol_code
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+ - code_alpaca
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+ base_model: meta-llama/Llama-2-7b-hf
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+ ---
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+
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+ # llama2-7b-coding-fft
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+
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+ This model is a **Full Fine-Tuned (FFT)** version of LLaMA2-7B on coding datasets, trained as part of replicating the [Mask Fine-Tuning (MFT) paper](https://arxiv.org/abs/2503.22764v1).
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+
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+ ## Model Details
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+
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+ - **Base Model:** meta-llama/Llama-2-7b-hf
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+ - **Training Type:** Full Fine-Tuning (FFT)
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+ - **Domain:** Coding
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+ - **Hardware:** TPU v4-8
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+ - **Training Framework:** PyTorch + torch_xla
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+
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+ ## Training Data
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+
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+ The model was trained on 30,000 samples from three coding datasets (matching the paper):
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+ - **Tulu 3 Persona Python:** 10,000 samples
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+ - **Evol CodeAlpaca:** 10,000 samples
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+ - **Code-Alpaca:** 10,000 samples
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+
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+ ## Training Configuration
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+
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+ - **Epochs:** 2
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+ - **Sequence Length:** 4096
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+ - **Learning Rate:** 2e-5
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+ - **Batch Size:** 8 (effective)
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+ - **Optimizer:** AdamW
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+ - **LR Scheduler:** Linear with warmup
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+ - **Mixed Precision:** bfloat16
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+
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+ ## Training Results
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+
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+ - **Final Loss:** 0.15353151041666666
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+ - **Final Perplexity:** 1.1673020833333334
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+ - **Training Time:** ~7 hours on TPU v4-8
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+ - **Total Steps:** 7500
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+
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+ ### Loss Progression
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+ - Epoch 0: 0.42591484375
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+ - Epoch 1: 0.15353151041666666
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+
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+ ## Intended Use
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+
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+ This model serves as the **FFT baseline** for the Mask Fine-Tuning paper replication. It will be evaluated on:
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+ - **HumanEval** (code generation benchmark)
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+ - Target: Match paper's FFT baseline of 29.3%
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+
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+ ## Evaluation
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+
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+ Evaluation on HumanEval is pending. Results will be updated here once available.
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+
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+ ## Citation
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+
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+ If you use this model, please cite the original MFT paper:
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+
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+ ```bibtex
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+ @article{mft2025,
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+ title={Mask Fine-Tuning},
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+ author={[Authors from paper]},
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+ journal={arXiv preprint arXiv:2503.22764v1},
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+ year={2025}
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+ }
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+ ```
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+
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+ ## Reproducibility
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+
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+ Training configuration and code available at: [GitHub Repository](https://github.com/chrisfrancisque/mft-tpu)
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+
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+ ## License
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+
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+ This model inherits the LLaMA 2 Community License from the base model.
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+ "_name_or_path": "meta-llama/Llama-2-7b-hf",
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+ "LlamaForCausalLM"
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+ ],
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+ "attention_bias": false,
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+ "eos_token_id": 2,
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+ "gradient_checkpointing": false,
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+ "initializer_range": 0.02,
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+ "model_type": "llama",
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+ "num_attention_heads": 32,
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+ "num_hidden_layers": 32,
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+ "num_key_value_heads": 32,
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+ "pretraining_tp": 1,
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+ "rms_norm_eps": 1e-05,
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+ "rope_scaling": null,
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+ "rope_theta": 10000.0,
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+ "torch_dtype": "bfloat16",
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+ "transformers_version": "4.35.0",
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+ "use_cache": false,
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+ "vocab_size": 32000
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+ }
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