---
base_model: meta-llama/Meta-Llama-3-8B
datasets:
- llama-duo/synth_coding_dataset_dedup
library_name: peft
license: llama3
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
model-index:
- name: llama3-8b-coding-gpt4o-100k
  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. -->

# llama3-8b-coding-gpt4o-100k

This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) on the llama-duo/synth_coding_dataset_dedup dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5174

## 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: 0.002
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.4861        | 1.0   | 135  | 1.2495          |
| 0.458         | 2.0   | 270  | 1.2390          |
| 0.4423        | 3.0   | 405  | 1.2549          |
| 0.4244        | 4.0   | 540  | 1.2665          |
| 0.4051        | 5.0   | 675  | 1.2714          |
| 0.3815        | 6.0   | 810  | 1.2959          |
| 0.3546        | 7.0   | 945  | 1.3560          |
| 0.3233        | 8.0   | 1080 | 1.4125          |
| 0.2969        | 9.0   | 1215 | 1.4809          |
| 0.2818        | 10.0  | 1350 | 1.5174          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.2.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1