---
base_model: unsloth/llama-3-8b
library_name: peft
license: llama3
tags:
- unsloth
- generated_from_trainer
model-index:
- name: Meta-Llama-3-8B_magiccoder_default
  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. -->

# Meta-Llama-3-8B_magiccoder_default

This model is a fine-tuned version of [unsloth/llama-3-8b](https://huggingface.co/unsloth/llama-3-8b) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2697

## 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: 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 |
|:-------------:|:------:|:----:|:---------------:|
| 1.2592        | 0.0259 | 4    | 1.4263          |
| 1.4281        | 0.0518 | 8    | 1.4063          |
| 1.3795        | 0.0777 | 12   | 1.3824          |
| 1.3751        | 0.1036 | 16   | 1.3937          |
| 1.4053        | 0.1296 | 20   | 1.3523          |
| 1.2927        | 0.1555 | 24   | 1.3474          |
| 1.3619        | 0.1814 | 28   | 1.3529          |
| 1.3533        | 0.2073 | 32   | 1.3629          |
| 1.3627        | 0.2332 | 36   | 1.3636          |
| 1.4408        | 0.2591 | 40   | 1.3531          |
| 1.3744        | 0.2850 | 44   | 1.3395          |
| 1.2658        | 0.3109 | 48   | 1.3364          |
| 1.3364        | 0.3368 | 52   | 1.3400          |
| 1.3765        | 0.3628 | 56   | 1.3391          |
| 1.3427        | 0.3887 | 60   | 1.3370          |
| 1.3975        | 0.4146 | 64   | 1.3329          |
| 1.2595        | 0.4405 | 68   | 1.3325          |
| 1.3291        | 0.4664 | 72   | 1.3312          |
| 1.2702        | 0.4923 | 76   | 1.3323          |
| 1.3527        | 0.5182 | 80   | 1.3213          |
| 1.2799        | 0.5441 | 84   | 1.3154          |
| 1.3082        | 0.5700 | 88   | 1.3099          |
| 1.4042        | 0.5960 | 92   | 1.3089          |
| 1.2221        | 0.6219 | 96   | 1.3048          |
| 1.3079        | 0.6478 | 100  | 1.3017          |
| 1.2165        | 0.6737 | 104  | 1.2970          |
| 1.239         | 0.6996 | 108  | 1.2941          |
| 1.2528        | 0.7255 | 112  | 1.2877          |
| 1.2932        | 0.7514 | 116  | 1.2859          |
| 1.2762        | 0.7773 | 120  | 1.2804          |
| 1.2914        | 0.8032 | 124  | 1.2791          |
| 1.2835        | 0.8291 | 128  | 1.2755          |
| 1.2735        | 0.8551 | 132  | 1.2731          |
| 1.2264        | 0.8810 | 136  | 1.2722          |
| 1.2637        | 0.9069 | 140  | 1.2713          |
| 1.2133        | 0.9328 | 144  | 1.2704          |
| 1.2379        | 0.9587 | 148  | 1.2699          |
| 1.2131        | 0.9846 | 152  | 1.2697          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1