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README.md

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+---
+library_name: transformers
+license: other
+base_model: meta-llama/Llama-3.1-8B
+language: en
+datasets:
+  - QizhiPei/MathFusionQA
+tags:
+- llama-factory
+- full
+pipeline_tag: text-generation
+model-index:
+- name: Llama3.1-8B-Middo-Alpaca
+  results: []
+---
+
+# Llama3.1-8B-Middo-Alpaca
+
+Paper: [Middo: Model-Informed Dynamic Data Optimization for Enhanced LLM Fine-Tuning via Closed-Loop Learning](https://arxiv.org/abs/2508.21589)
+
+Code: https://github.com/Word2VecT/Middo
+
+This model is a fine-tuned version of [meta-llama/Llama-3.1-8B](https://huggingface.co/meta-llama/Llama-3.1-8B) on the [MiddOptimzed/llama_alpaca](https://huggingface.co/datasets/Word2Li/MiddOptimized/viewer/default/mistral_alpaca) dataset.
+
+## Model description
+
+More information needed
+
+## Training and evaluation data
+
+### Training data
+
+Middo Optimized [Alpaca](https://huggingface.co/datasets/tatsu-lab/alpaca) on [meta-llama/Llama-3.1-8B](https://huggingface.co/meta-llama/Llama-3.1-8B).
+
+### Evaluation data
+
+- General
+  - MMLU
+  - IFEval
+- Math
+  - GSM8K
+  - MATH
+- Code
+  - HumanEval
+  - MBPP
+- Reasoning
+  - Hellaswag
+  - GPQA
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+
+- learning_rate: 2e-05
+- train_batch_size: 4
+- eval_batch_size: 8
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 8
+- gradient_accumulation_steps: 8
+- total_train_batch_size: 256
+- total_eval_batch_size: 64
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_ratio: 0.03
+- num_epochs: 1.0
+
+### Training results
+
+### Framework versions
+
+- Transformers 4.45.2
+- Pytorch 2.5.1+cu121
+- Datasets 2.21.0
+- Tokenizers 0.20.1

all_results.json

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+    "total_flos": 8.515440547840655e+17,
+    "train_loss": 1.1814873923195732,
+    "train_runtime": 2241.1241,
+    "train_samples_per_second": 25.717,
+    "train_steps_per_second": 0.1
+}

config.json

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+  "architectures": [
+    "LlamaForCausalLM"
+  ],
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+  "attention_dropout": 0.0,
+  "bos_token_id": 128000,
+  "eos_token_id": 128001,
+  "head_dim": 128,
+  "hidden_act": "silu",
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+  "initializer_range": 0.02,
+  "intermediate_size": 14336,
+  "max_position_embeddings": 131072,
+  "mlp_bias": false,
+  "model_type": "llama",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 8,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": {
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+    "high_freq_factor": 4.0,
+    "low_freq_factor": 1.0,
+    "original_max_position_embeddings": 8192,
+    "rope_type": "llama3"
+  },
+  "rope_theta": 500000.0,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.45.2",
+  "use_cache": false,
+  "vocab_size": 128256
+}

generation_config.json

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+  "do_sample": true,
+  "eos_token_id": 128001,
+  "temperature": 0.6,
+  "top_p": 0.9,
+  "transformers_version": "4.45.2"
+}

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train_results.json

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