---
license: llama2
base_model: meta-llama/CodeLlama-13b-Instruct-hf
tags:
- alignment-handbook
- generated_from_trainer
datasets:
- meng-lab/CodeLlama-13B-Instruct-xsum
model-index:
- name: CodeLlama-13b-Instruct-sft-5e-3-epoch-100-xsum
  results: []
---

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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/54db35e9)
# CodeLlama-13b-Instruct-sft-5e-3-epoch-100-xsum

This model is a fine-tuned version of [meta-llama/CodeLlama-13b-Instruct-hf](https://huggingface.co/meta-llama/CodeLlama-13b-Instruct-hf) on the meng-lab/CodeLlama-13B-Instruct-xsum dataset.

## 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



### Framework versions

- Transformers 4.43.2
- Pytorch 2.1.2
- Datasets 3.0.1
- Tokenizers 0.19.1