---
library_name: peft
license: llama3.2
base_model: meta-llama/Llama-3.2-1B
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: LLama3-1B-finetuning
  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. -->

# LLama3-1B-finetuning

This model is a fine-tuned version of [meta-llama/Llama-3.2-1B](https://huggingface.co./meta-llama/Llama-3.2-1B) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3472
- Accuracy: 0.8694
- F1 Macro: 0.8692

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
| 1.3459        | 1.0   | 360  | 0.7530          | 0.6667   | 0.6615   |
| 0.8291        | 2.0   | 720  | 0.4807          | 0.8021   | 0.7951   |
| 0.8198        | 3.0   | 1080 | 0.4037          | 0.8306   | 0.8255   |
| 0.6597        | 4.0   | 1440 | 0.4082          | 0.8292   | 0.8270   |
| 0.5621        | 5.0   | 1800 | 0.3817          | 0.8438   | 0.8410   |
| 0.5646        | 6.0   | 2160 | 0.3784          | 0.8472   | 0.8453   |
| 0.4532        | 7.0   | 2520 | 0.3879          | 0.8431   | 0.8401   |


### Framework versions

- PEFT 0.14.0
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0