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---
base_model: meta-llama/Llama-3.1-8B-Instruct
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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