---
library_name: peft
license: llama3.2
base_model: meta-llama/Llama-3.2-3B
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: LLama3-1B-finetuning-italian-version
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# LLama3-1B-finetuning-italian-version

This model is a fine-tuned version of [meta-llama/Llama-3.2-3B](https://huggingface.co./meta-llama/Llama-3.2-3B) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4414
- Model Preparation Time: 0.0045
- Accuracy: 0.8313
- F1 Macro: 0.8354

## 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 OptimizerNames.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 | Model Preparation Time | Accuracy | F1 Macro |
|:-------------:|:-----:|:----:|:---------------:|:----------------------:|:--------:|:--------:|
| 0.9162        | 1.0   | 368  | 0.8379          | 0.0045                 | 0.6361   | 0.6334   |
| 0.5201        | 2.0   | 736  | 0.5242          | 0.0045                 | 0.7782   | 0.7849   |
| 0.3988        | 3.0   | 1104 | 0.4936          | 0.0045                 | 0.7993   | 0.8024   |
| 0.3288        | 4.0   | 1472 | 0.4774          | 0.0045                 | 0.8007   | 0.8084   |
| 0.3602        | 5.0   | 1840 | 0.4858          | 0.0045                 | 0.8034   | 0.8103   |


### Framework versions

- PEFT 0.14.0
- Transformers 4.48.2
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0