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README.md

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+---
+base_model: /home/jovyan/workspace/PipeDec/checkpoint/Llama-3.1-8B-Instruct-sft-5e-3-epoch-100-humaneval-stage-2
+tags:
+- alignment-handbook
+- generated_from_trainer
+datasets:
+- meng-lab/Llama-3.1-8B-Instruct-humaneval
+model-index:
+- name: Llama-3.1-8B-Instruct-sft-5e-3-epoch-100-humaneval-stage-3
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/uva-llm/huggingface/runs/86389vz6)
+# Llama-3.1-8B-Instruct-sft-5e-3-epoch-100-humaneval-stage-3
+
+This model is a fine-tuned version of [/home/jovyan/workspace/PipeDec/checkpoint/Llama-3.1-8B-Instruct-sft-5e-3-epoch-100-humaneval-stage-2](https://huggingface.co//home/jovyan/workspace/PipeDec/checkpoint/Llama-3.1-8B-Instruct-sft-5e-3-epoch-100-humaneval-stage-2) on the meng-lab/Llama-3.1-8B-Instruct-humaneval dataset.
+It achieves the following results on the evaluation set:
+- Loss: 11.0822
+- Loss Three Hop Layer 8 Head: 3.3949
+- Loss Three Hop Layer 16 Head: 2.9406
+- Loss Three Hop Layer 24 Head: 2.6311
+- Loss Three Hop Layer 32 Head: 2.4800
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 0.005
+- train_batch_size: 1
+- eval_batch_size: 2
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 8
+- gradient_accumulation_steps: 16
+- total_train_batch_size: 128
+- total_eval_batch_size: 16
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 100
+
+### Training results
+
+| Training Loss | Epoch   | Step | Validation Loss | Loss Three Hop Layer 8 Head | Loss Three Hop Layer 16 Head | Loss Three Hop Layer 24 Head | Loss Three Hop Layer 32 Head |
+|:-------------:|:-------:|:----:|:---------------:|:---------------------------:|:----------------------------:|:----------------------------:|:----------------------------:|
+| 17.1204       | 9.6677  | 200  | 17.4024         | 4.0165                      | 3.6938                       | 5.0117                       | 5.0980                       |
+| 11.7831       | 19.3353 | 400  | 12.4640         | 3.8214                      | 3.1283                       | 2.8095                       | 3.0563                       |
+| 11.1082       | 29.0030 | 600  | 12.3118         | 3.4779                      | 3.1955                       | 2.9590                       | 2.9857                       |
+| 10.9205       | 38.6707 | 800  | 11.9277         | 3.7709                      | 3.0051                       | 2.8893                       | 2.6454                       |
+| 10.1281       | 48.3384 | 1000 | 11.6923         | 3.4574                      | 2.9719                       | 2.8398                       | 2.7656                       |
+| 9.4147        | 58.0060 | 1200 | 11.2543         | 3.4058                      | 2.9891                       | 2.6593                       | 2.5635                       |
+| 8.9315        | 67.6737 | 1400 | 11.0952         | 3.3972                      | 2.9370                       | 2.6327                       | 2.4895                       |
+| 8.9092        | 77.3414 | 1600 | 11.1042         | 3.4010                      | 2.9454                       | 2.6344                       | 2.4875                       |
+| 8.8371        | 87.0091 | 1800 | 11.0849         | 3.3957                      | 2.9410                       | 2.6311                       | 2.4803                       |
+| 8.8213        | 96.6767 | 2000 | 11.0822         | 3.3949                      | 2.9406                       | 2.6311                       | 2.4800                       |
+
+
+### Framework versions
+
+- Transformers 4.43.2
+- Pytorch 2.6.0+cu124
+- Datasets 3.2.0
+- Tokenizers 0.19.1

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