---
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
datasets:
- generator
library_name: peft
license: llama3.1
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: ft-raft-lora
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# ft-raft-lora

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 generator dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1402

## 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: 1399
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- training_steps: 500

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.8153        | 0.8696 | 20   | 1.6376          |
| 1.3735        | 1.7391 | 40   | 1.1018          |
| 0.7809        | 2.6087 | 60   | 0.4950          |
| 0.3055        | 3.4783 | 80   | 0.2025          |
| 0.1425        | 4.3478 | 100  | 0.1491          |
| 0.105         | 5.2174 | 120  | 0.1422          |
| 0.0755        | 6.0870 | 140  | 0.1377          |
| 0.0602        | 6.9565 | 160  | 0.1402          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1