---
library_name: peft
license: llama3.2
base_model: meta-llama/Llama-3.2-11B-Vision-Instruct
tags:
- trl
- sft
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: fine-tuned-visionllama
  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. -->

# fine-tuned-visionllama

This model is a fine-tuned version of [meta-llama/Llama-3.2-11B-Vision-Instruct](https://huggingface.co/meta-llama/Llama-3.2-11B-Vision-Instruct) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2764
- Accuracy: 0.0262
- F1: 0.0263

## 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: 0.0002
- 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: constant
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 2

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
| 0.6989        | 0.9778 | 22   | 0.6079          | 0.0001   | 0.0001 |
| 0.3177        | 1.9556 | 44   | 0.2764          | 0.0262   | 0.0263 |


### Framework versions

- PEFT 0.13.0
- Transformers 4.45.1
- Pytorch 2.4.0+cu121
- Datasets 3.0.1
- Tokenizers 0.20.3