---
library_name: peft
license: llama3.1
base_model: meta-llama/Llama-3.1-8B-Instruct
tags:
- generated_from_trainer
model-index:
- name: Best_Model_256_Instruct
  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. -->

# Best_Model_256_Instruct

This model is a fine-tuned version of [meta-llama/Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5285

## 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: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| No log        | 0.2544 | 29   | 1.0916          |
| No log        | 0.5088 | 58   | 0.7436          |
| No log        | 0.7632 | 87   | 0.6517          |
| No log        | 1.0175 | 116  | 0.5922          |
| No log        | 1.2719 | 145  | 0.5741          |
| No log        | 1.5263 | 174  | 0.5641          |
| No log        | 1.7807 | 203  | 0.5365          |
| No log        | 2.0351 | 232  | 0.5276          |
| No log        | 2.2895 | 261  | 0.5263          |
| No log        | 2.5439 | 290  | 0.5269          |
| No log        | 2.7982 | 319  | 0.5387          |
| No log        | 3.0526 | 348  | 0.5285          |


### Framework versions

- PEFT 0.14.0
- Transformers 4.52.4
- Pytorch 2.7.0+cu126
- Datasets 3.6.0
- Tokenizers 0.21.0