---
license: llama2
base_model: meta-llama/CodeLlama-34b-Instruct-hf
tags:
- alignment-handbook
- generated_from_trainer
datasets:
- meng-lab/CodeLlama-34B-Instruct-humaneval
model-index:
- name: CodeLlama-34b-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
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[<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/93nixyw1)
# CodeLlama-34b-Instruct-sft-5e-3-epoch-100-human-eval-final

This model is a fine-tuned version of [meta-llama/CodeLlama-34b-Instruct-hf](https://huggingface.co/meta-llama/CodeLlama-34b-Instruct-hf) on the meng-lab/CodeLlama-34B-Instruct-humaneval dataset.
It achieves the following results on the evaluation set:
- Loss: 3.7616
- Loss Layer 6 Head: 1.0709
- Loss Layer 12 Head: 0.8047
- Loss Layer 18 Head: 0.7212
- Loss Layer 24 Head: 0.4396
- Loss Layer 30 Head: 0.3042
- Loss Layer 36 Head: 0.2040
- Loss Layer 42 Head: 0.1346

## 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 Layer 6 Head | Loss Layer 12 Head | Loss Layer 18 Head | Loss Layer 24 Head | Loss Layer 30 Head | Loss Layer 36 Head | Loss Layer 42 Head |
|:-------------:|:-------:|:----:|:---------------:|:-----------------:|:------------------:|:------------------:|:------------------:|:------------------:|:------------------:|:------------------:|
| 3.7028        | 9.1168  | 200  | 4.6352          | 1.4035            | 0.8311             | 1.0429             | 0.4931             | 0.4457             | 0.2349             | 0.1599             |
| 2.736         | 18.2336 | 400  | 4.7219          | 1.2158            | 0.8316             | 0.7490             | 1.0869             | 0.3238             | 0.2666             | 0.1723             |
| 2.0128        | 27.3504 | 600  | 3.8953          | 1.1598            | 0.8030             | 0.7230             | 0.4451             | 0.3500             | 0.2027             | 0.1459             |
| 3.3605        | 36.4672 | 800  | 4.9203          | 1.1038            | 0.8175             | 1.6655             | 0.4410             | 0.3091             | 0.2055             | 0.1365             |
| 2.5177        | 45.5840 | 1000 | 4.2388          | 1.0907            | 0.8042             | 1.1115             | 0.4403             | 0.3038             | 0.2217             | 0.1412             |
| 2.0743        | 54.7009 | 1200 | 3.9221          | 1.0727            | 0.8050             | 0.8689             | 0.4418             | 0.3012             | 0.2044             | 0.1362             |
| 1.8844        | 63.8177 | 1400 | 3.8140          | 1.0723            | 0.8028             | 0.7729             | 0.4389             | 0.3045             | 0.2036             | 0.1350             |
| 1.8019        | 72.9345 | 1600 | 3.7777          | 1.0726            | 0.8038             | 0.7376             | 0.4401             | 0.3042             | 0.2032             | 0.1345             |
| 1.7339        | 82.0513 | 1800 | 3.7662          | 1.0703            | 0.8056             | 0.7246             | 0.4394             | 0.3041             | 0.2042             | 0.1347             |
| 1.6981        | 91.1681 | 2000 | 3.7616          | 1.0709            | 0.8047             | 0.7212             | 0.4396             | 0.3042             | 0.2040             | 0.1346             |


### Framework versions

- Transformers 4.43.2
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.19.1