---
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
library_name: peft
license: llama3.1
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: Llama-31-8B_task-3_180-samples_config-1_full
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Llama-31-8B_task-3_180-samples_config-1_full

This model is a fine-tuned version of [meta-llama/Meta-Llama-3.1-8B-Instruct](https://huggingface.co./meta-llama/Meta-Llama-3.1-8B-Instruct) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4002

## 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: 0.0001
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 8
- total_train_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: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.6392        | 1.0   | 17   | 1.6279          |
| 1.4618        | 2.0   | 34   | 1.4343          |
| 1.2006        | 3.0   | 51   | 1.2241          |
| 1.0799        | 4.0   | 68   | 1.1761          |
| 1.0615        | 5.0   | 85   | 1.1524          |
| 1.0045        | 6.0   | 102  | 1.1361          |
| 0.9831        | 7.0   | 119  | 1.1392          |
| 0.8698        | 8.0   | 136  | 1.1567          |
| 0.7759        | 9.0   | 153  | 1.1918          |
| 0.7296        | 10.0  | 170  | 1.2537          |
| 0.6747        | 11.0  | 187  | 1.2852          |
| 0.4777        | 12.0  | 204  | 1.3877          |
| 0.5052        | 13.0  | 221  | 1.4002          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.1.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1