---
license: llama3.1
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
model-index:
- name: llama3.1_8b_bwgenerator
  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. -->

# llama3.1_8b_bwgenerator

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 an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1141

## 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: 0.0003
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 32
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.1896        | 0.1214 | 20   | 0.3793          |
| 0.3219        | 0.2427 | 40   | 0.2798          |
| 0.2583        | 0.3641 | 60   | 0.2367          |
| 0.2204        | 0.4854 | 80   | 0.2002          |
| 0.1785        | 0.6068 | 100  | 0.1566          |
| 0.1488        | 0.7281 | 120  | 0.1404          |
| 0.1391        | 0.8495 | 140  | 0.1348          |
| 0.1332        | 0.9708 | 160  | 0.1310          |
| 0.1281        | 1.0922 | 180  | 0.1254          |
| 0.1246        | 1.2135 | 200  | 0.1229          |
| 0.1229        | 1.3349 | 220  | 0.1200          |
| 0.1202        | 1.4562 | 240  | 0.1179          |
| 0.1185        | 1.5776 | 260  | 0.1164          |
| 0.1166        | 1.6989 | 280  | 0.1154          |
| 0.1165        | 1.8203 | 300  | 0.1143          |
| 0.1155        | 1.9416 | 320  | 0.1141          |


### Framework versions

- PEFT 0.10.0
- Transformers 4.44.0
- Pytorch 2.3.0+cu121
- Datasets 2.14.7
- Tokenizers 0.19.1