---
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-100k
  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-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_classification_dataset_dedup dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0032

## 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: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.9183        | 1.0   | 237  | 1.6517          |
| 0.8583        | 2.0   | 474  | 1.6295          |
| 0.8179        | 3.0   | 711  | 1.6559          |
| 0.7533        | 4.0   | 948  | 1.6894          |
| 0.716         | 5.0   | 1185 | 1.7251          |
| 0.6876        | 6.0   | 1422 | 1.7830          |
| 0.6344        | 7.0   | 1659 | 1.8557          |
| 0.591         | 8.0   | 1896 | 1.9240          |
| 0.5677        | 9.0   | 2133 | 1.9842          |
| 0.5648        | 10.0  | 2370 | 2.0032          |


### Framework versions

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