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

# lora_final

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: 1.2166

## 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: 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: cosine
- lr_scheduler_warmup_ratio: 0.02
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.2611        | 0.0259 | 4    | 1.3885          |
| 1.3239        | 0.0518 | 8    | 1.3166          |
| 1.2605        | 0.0777 | 12   | 1.2847          |
| 1.2849        | 0.1036 | 16   | 1.2750          |
| 1.2928        | 0.1296 | 20   | 1.2562          |
| 1.1904        | 0.1555 | 24   | 1.2448          |
| 1.2444        | 0.1814 | 28   | 1.2414          |
| 1.2182        | 0.2073 | 32   | 1.2368          |
| 1.2447        | 0.2332 | 36   | 1.2359          |
| 1.2958        | 0.2591 | 40   | 1.2332          |
| 1.2491        | 0.2850 | 44   | 1.2297          |
| 1.1667        | 0.3109 | 48   | 1.2305          |
| 1.2285        | 0.3368 | 52   | 1.2287          |
| 1.2667        | 0.3628 | 56   | 1.2263          |
| 1.2466        | 0.3887 | 60   | 1.2270          |
| 1.3088        | 0.4146 | 64   | 1.2266          |
| 1.1579        | 0.4405 | 68   | 1.2262          |
| 1.2358        | 0.4664 | 72   | 1.2229          |
| 1.1688        | 0.4923 | 76   | 1.2220          |
| 1.2594        | 0.5182 | 80   | 1.2215          |
| 1.1863        | 0.5441 | 84   | 1.2196          |
| 1.229         | 0.5700 | 88   | 1.2200          |
| 1.3299        | 0.5960 | 92   | 1.2196          |
| 1.1395        | 0.6219 | 96   | 1.2187          |
| 1.2305        | 0.6478 | 100  | 1.2189          |
| 1.1493        | 0.6737 | 104  | 1.2192          |
| 1.1693        | 0.6996 | 108  | 1.2191          |
| 1.1856        | 0.7255 | 112  | 1.2189          |
| 1.2429        | 0.7514 | 116  | 1.2183          |
| 1.2234        | 0.7773 | 120  | 1.2181          |
| 1.243         | 0.8032 | 124  | 1.2178          |
| 1.2387        | 0.8291 | 128  | 1.2172          |
| 1.2366        | 0.8551 | 132  | 1.2168          |
| 1.1838        | 0.8810 | 136  | 1.2167          |
| 1.1884        | 0.9069 | 140  | 1.2167          |
| 1.1714        | 0.9328 | 144  | 1.2167          |
| 1.2058        | 0.9587 | 148  | 1.2166          |
| 1.1725        | 0.9846 | 152  | 1.2166          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.44.2
- Pytorch 2.3.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1