---
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-2_auto
  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-2_auto

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: 0.5974

## 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: 16
- total_train_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: 50

### Training results

| Training Loss | Epoch   | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 2.1694        | 0.9412  | 8    | 2.0003          |
| 1.1443        | 2.0     | 17   | 0.8652          |
| 0.5201        | 2.9412  | 25   | 0.4725          |
| 0.2979        | 4.0     | 34   | 0.3815          |
| 0.3128        | 4.9412  | 42   | 0.3738          |
| 0.3107        | 6.0     | 51   | 0.3410          |
| 0.2488        | 6.9412  | 59   | 0.3388          |
| 0.252         | 8.0     | 68   | 0.3387          |
| 0.2324        | 8.9412  | 76   | 0.3474          |
| 0.1655        | 10.0    | 85   | 0.3932          |
| 0.1782        | 10.9412 | 93   | 0.4127          |
| 0.0536        | 12.0    | 102  | 0.4492          |
| 0.0425        | 12.9412 | 110  | 0.5433          |
| 0.0347        | 14.0    | 119  | 0.6090          |
| 0.0231        | 14.9412 | 127  | 0.5974          |


### Framework versions

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