---
base_model: meta-llama/Meta-Llama-3.1-8B
datasets:
- llama-duo/synth_closed_qa_dataset_dedup
library_name: peft
license: llama3.1
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
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# llama3.1-8b-closedqa-gpt4o-100k

This model is a fine-tuned version of [meta-llama/Meta-Llama-3.1-8B](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B) on the llama-duo/synth_closed_qa_dataset_dedup dataset.
It achieves the following results on the evaluation set:
- Loss: 3.8424

## 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: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.9422        | 0.9991 | 582  | 1.9762          |
| 0.8939        | 2.0    | 1165 | 2.0232          |
| 0.8255        | 2.9991 | 1747 | 2.1086          |
| 0.7584        | 4.0    | 2330 | 2.2541          |
| 0.6928        | 4.9991 | 2912 | 2.4424          |
| 0.6102        | 6.0    | 3495 | 2.7089          |
| 0.5466        | 6.9991 | 4077 | 3.0554          |
| 0.5038        | 8.0    | 4660 | 3.4053          |
| 0.4624        | 8.9991 | 5242 | 3.6952          |
| 0.454         | 9.9914 | 5820 | 3.8424          |


### Framework versions

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