---
license: gemma
library_name: peft
tags:
- generated_from_trainer
base_model: google/paligemma-3b-pt-224
datasets:
- vq_av2
model-index:
- name: paligemma-vqa
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# paligemma-vqa

This model is a fine-tuned version of [google/paligemma-3b-pt-224](https://huggingface.co/google/paligemma-3b-pt-224) on the vq_av2 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5071

## 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: 0.0001
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 2

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.5618        | 0.5886 | 1000 | 0.5531          |
| 0.5268        | 1.1772 | 2000 | 0.5335          |
| 0.5099        | 1.7657 | 3000 | 0.5071          |


### Framework versions

- PEFT 0.11.1
- Transformers 4.41.1
- Pytorch 2.2.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1