---
license: llama3
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
base_model: meta-llama/Meta-Llama-3-8B-Instruct
model-index:
- name: unaligned
  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. -->

# unaligned

This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0709

## 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: 0.0002
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 2048

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.1154        | 0.1110 | 100  | 0.1172          |
| 0.092         | 0.2220 | 200  | 0.1028          |
| 0.0462        | 0.3330 | 300  | 0.0992          |
| 0.0482        | 0.4440 | 400  | 0.0755          |
| 0.043         | 0.5550 | 500  | 0.0794          |
| 0.0476        | 0.6660 | 600  | 0.0628          |
| 0.0482        | 0.7770 | 700  | 0.0821          |
| 0.0484        | 0.8880 | 800  | 0.0691          |
| 0.0448        | 0.9990 | 900  | 0.0829          |
| 0.0214        | 1.1100 | 1000 | 0.0720          |
| 0.0439        | 1.2210 | 1100 | 0.0635          |
| 0.0364        | 1.3320 | 1200 | 0.0713          |
| 0.0497        | 1.4430 | 1300 | 0.0669          |
| 0.0455        | 1.5540 | 1400 | 0.0672          |
| 0.0614        | 1.6650 | 1500 | 0.0805          |
| 0.0416        | 1.7761 | 1600 | 0.0669          |
| 0.0367        | 1.8871 | 1700 | 0.0716          |
| 0.0578        | 1.9981 | 1800 | 0.0684          |
| 0.0358        | 2.1091 | 1900 | 0.0705          |
| 0.0326        | 2.2201 | 2000 | 0.0709          |


### Framework versions

- PEFT 0.11.1
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1