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

# Llama-Instruct-8B

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: 0.2965

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.PAGED_ADAMW_8BIT with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 2.1139        | 0.1144 | 50   | 1.8861          |
| 1.3487        | 0.2288 | 100  | 0.6872          |
| 0.4797        | 0.3432 | 150  | 0.4065          |
| 0.3914        | 0.4577 | 200  | 0.3877          |
| 0.3808        | 0.5721 | 250  | 0.3773          |
| 0.3682        | 0.6865 | 300  | 0.3622          |
| 0.3539        | 0.8009 | 350  | 0.3459          |
| 0.3333        | 0.9153 | 400  | 0.3344          |
| 0.3278        | 1.0297 | 450  | 0.3261          |
| 0.3227        | 1.1442 | 500  | 0.3215          |
| 0.3182        | 1.2586 | 550  | 0.3185          |
| 0.315         | 1.3730 | 600  | 0.3156          |
| 0.3117        | 1.4874 | 650  | 0.3142          |
| 0.3108        | 1.6018 | 700  | 0.3122          |
| 0.3083        | 1.7162 | 750  | 0.3113          |
| 0.3086        | 1.8307 | 800  | 0.3089          |
| 0.3083        | 1.9451 | 850  | 0.3075          |
| 0.3054        | 2.0595 | 900  | 0.3070          |
| 0.3043        | 2.1739 | 950  | 0.3054          |
| 0.301         | 2.2883 | 1000 | 0.3040          |
| 0.3023        | 2.4027 | 1050 | 0.3034          |
| 0.2988        | 2.5172 | 1100 | 0.3025          |
| 0.2988        | 2.6316 | 1150 | 0.3023          |
| 0.2988        | 2.7460 | 1200 | 0.3007          |
| 0.2987        | 2.8604 | 1250 | 0.3002          |
| 0.2974        | 2.9748 | 1300 | 0.2999          |
| 0.2966        | 3.0892 | 1350 | 0.2991          |
| 0.2966        | 3.2037 | 1400 | 0.2988          |
| 0.2963        | 3.3181 | 1450 | 0.2981          |
| 0.295         | 3.4325 | 1500 | 0.2979          |
| 0.2931        | 3.5469 | 1550 | 0.2974          |
| 0.2944        | 3.6613 | 1600 | 0.2972          |
| 0.2937        | 3.7757 | 1650 | 0.2967          |
| 0.2904        | 3.8902 | 1700 | 0.2965          |


### Framework versions

- PEFT 0.14.0
- Transformers 4.50.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1