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---
license: llama3.1
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-human-eval-final
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/b08pi5fy)
# Llama-3.1-8B-Instruct-sft-5e-3-epoch-100-human-eval-final
This model is a fine-tuned version of [meta-llama/Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct) on the meng-lab/Llama-3.1-8B-Instruct-humaneval dataset.
It achieves the following results on the evaluation set:
- Loss: 5.3754
- Loss Layer 4 Head: 1.6774
- Loss Layer 8 Head: 1.3806
- Loss Layer 12 Head: 1.2795
- Loss Layer 16 Head: 0.6378
- Loss Layer 20 Head: 0.3110
- Loss Layer 24 Head: 0.1844
- Loss Layer 28 Head: 0.0864
## 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: 4
- gradient_accumulation_steps: 32
- total_train_batch_size: 128
- total_eval_batch_size: 8
- 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 Layer 4 Head | Loss Layer 8 Head | Loss Layer 12 Head | Loss Layer 16 Head | Loss Layer 20 Head | Loss Layer 24 Head | Loss Layer 28 Head |
|:-------------:|:-------:|:----:|:---------------:|:-----------------:|:-----------------:|:------------------:|:------------------:|:------------------:|:------------------:|:------------------:|
| 7.7477 | 9.6823 | 200 | 7.6952 | 1.9941 | 1.7442 | 1.9609 | 1.0923 | 0.4414 | 0.2459 | 0.4381 |
| 5.8078 | 19.3646 | 400 | 6.4289 | 1.9090 | 1.5288 | 1.4099 | 0.9812 | 0.3976 | 0.2383 | 0.1448 |
| 4.8435 | 29.0469 | 600 | 5.9964 | 1.8480 | 1.5236 | 1.3836 | 0.6737 | 0.3976 | 0.2537 | 0.1092 |
| 4.6084 | 38.7292 | 800 | 6.0069 | 1.8460 | 1.7121 | 1.3111 | 0.6743 | 0.3436 | 0.2146 | 0.0977 |
| 4.0625 | 48.4115 | 1000 | 5.7159 | 1.8920 | 1.4329 | 1.3107 | 0.6548 | 0.3220 | 0.1980 | 0.0920 |
| 3.7565 | 58.0938 | 1200 | 5.4530 | 1.7095 | 1.3997 | 1.2900 | 0.6451 | 0.3159 | 0.1877 | 0.0897 |
| 3.5758 | 67.7761 | 1400 | 5.4088 | 1.6897 | 1.3862 | 1.2843 | 0.6413 | 0.3125 | 0.1860 | 0.0880 |
| 3.5369 | 77.4584 | 1600 | 5.3933 | 1.6839 | 1.3837 | 1.2815 | 0.6409 | 0.3124 | 0.1856 | 0.0870 |
| 3.51 | 87.1407 | 1800 | 5.3780 | 1.6781 | 1.3809 | 1.2799 | 0.6378 | 0.3111 | 0.1843 | 0.0865 |
| 3.4762 | 96.8230 | 2000 | 5.3754 | 1.6774 | 1.3806 | 1.2795 | 0.6378 | 0.3110 | 0.1844 | 0.0864 |
### Framework versions
- Transformers 4.43.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1
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