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---
base_model: meta-llama/Meta-Llama-3-8B
datasets:
- llama-duo/synth_closed_qa_dataset_dedup
library_name: peft
license: llama3
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
model-index:
- name: llama3.1-8b-closedqa-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. -->

# llama3.1-8b-closedqa-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_closed_qa_dataset_dedup dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1008

## 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: 8
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 0.8026        | 1.0   | 256  | 2.0456          |
| 0.7532        | 2.0   | 512  | 2.0313          |
| 0.7198        | 3.0   | 768  | 2.0404          |
| 0.7053        | 4.0   | 1024 | 2.0419          |
| 0.6831        | 5.0   | 1280 | 2.0541          |
| 0.6633        | 6.0   | 1536 | 2.0744          |
| 0.6595        | 7.0   | 1792 | 2.0814          |
| 0.6374        | 8.0   | 2048 | 2.0939          |
| 0.6277        | 9.0   | 2304 | 2.0994          |
| 0.616         | 10.0  | 2560 | 2.1008          |


### Framework versions

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