---
base_model: meta-llama/Llama-3.2-1B-Instruct
library_name: peft
license: llama3.2
tags:
- generated_from_trainer
model-index:
- name: Llama-3.2-1B-Instruct_v2
  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. -->

# Llama-3.2-1B-Instruct_v2

This model is a fine-tuned version of [meta-llama/Llama-3.2-1B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-1B-Instruct) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2356

## 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: 0.0005
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 30
- training_steps: 3000

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.4565        | 0.0333 | 100  | 0.4058          |
| 0.3313        | 0.0667 | 200  | 0.3428          |
| 0.3139        | 0.1    | 300  | 0.3192          |
| 0.2903        | 0.1333 | 400  | 0.3034          |
| 0.2639        | 0.1667 | 500  | 0.2944          |
| 0.2688        | 0.2    | 600  | 0.2869          |
| 0.3097        | 0.2333 | 700  | 0.2791          |
| 0.2462        | 0.2667 | 800  | 0.2735          |
| 0.3257        | 0.3    | 900  | 0.2684          |
| 0.2738        | 0.3333 | 1000 | 0.2638          |
| 0.2572        | 0.3667 | 1100 | 0.2598          |
| 0.234         | 0.4    | 1200 | 0.2566          |
| 0.2233        | 0.4333 | 1300 | 0.2537          |
| 0.2996        | 0.4667 | 1400 | 0.2515          |
| 0.2178        | 0.5    | 1500 | 0.2490          |
| 0.2251        | 0.5333 | 1600 | 0.2470          |
| 0.262         | 0.5667 | 1700 | 0.2450          |
| 0.2683        | 0.6    | 1800 | 0.2430          |
| 0.1966        | 0.6333 | 1900 | 0.2416          |
| 0.2451        | 0.6667 | 2000 | 0.2403          |
| 0.2247        | 0.7    | 2100 | 0.2393          |
| 0.1865        | 0.7333 | 2200 | 0.2384          |
| 0.2837        | 0.7667 | 2300 | 0.2378          |
| 0.2312        | 0.8    | 2400 | 0.2371          |
| 0.239         | 0.8333 | 2500 | 0.2365          |
| 0.2064        | 0.8667 | 2600 | 0.2362          |
| 0.208         | 0.9    | 2700 | 0.2358          |
| 0.2588        | 0.9333 | 2800 | 0.2356          |
| 0.2029        | 0.9667 | 2900 | 0.2356          |
| 0.2404        | 1.0    | 3000 | 0.2356          |


### Framework versions

- PEFT 0.13.2
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1