---
base_model: meta-llama/Meta-Llama-3-8B
datasets:
- llama-duo/synth_classification_dataset_dedup
library_name: peft
license: llama3
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
model-index:
- name: llama3-8b-classification-gpt4o-100k2
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# llama3-8b-classification-gpt4o-100k2

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_classification_dataset_dedup dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8048

## 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: 0.0002
- train_batch_size: 4
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- 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: 5

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.4428        | 0.9978 | 225  | 1.7488          |
| 1.3593        | 2.0    | 451  | 1.7692          |
| 1.3157        | 2.9978 | 676  | 1.7700          |
| 1.2688        | 4.0    | 902  | 1.7925          |
| 1.2699        | 4.9889 | 1125 | 1.8048          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1