---
library_name: peft
license: llama3.2
base_model: meta-llama/Llama-3.2-3B
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: LLama3-3B-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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# LLama3-3B-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: 0.4762
- Model Preparation Time: 0.0067
- Accuracy: 0.8388
- F1 Macro: 0.8459

## 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: 3.9922302694761015e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- 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: cosine
- lr_scheduler_warmup_ratio: 0.0960656012161834
- num_epochs: 7
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Accuracy | F1 Macro |
|:-------------:|:-----:|:----:|:---------------:|:----------------------:|:--------:|:--------:|
| 0.4458        | 1.0   | 735  | 0.4802          | 0.0067                 | 0.8034   | 0.8130   |
| 0.3723        | 2.0   | 1470 | 0.4281          | 0.0067                 | 0.8184   | 0.8270   |
| 0.2744        | 3.0   | 2205 | 0.4820          | 0.0067                 | 0.8218   | 0.8305   |
| 0.1358        | 4.0   | 2940 | 0.6884          | 0.0067                 | 0.8156   | 0.8254   |


### Framework versions

- PEFT 0.14.0
- Transformers 4.49.0
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0