README.md

---
license: gemma
base_model: google/paligemma-3b-pt-224
tags:
- generated_from_trainer
datasets:
- vq_av2
model-index:
- name: paligemma_vqa_lower
  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. -->

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/statking/huggingface/runs/w0sur7w6)
# paligemma_vqa_lower

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: 0.0131

## 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
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- 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: 1200
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 5.5759        | 0.1471 | 500  | 4.3404          |
| 0.2128        | 0.2943 | 1000 | 0.1315          |
| 0.0267        | 0.4414 | 1500 | 0.0261          |
| 0.0151        | 0.5886 | 2000 | 0.0157          |
| 0.0143        | 0.7357 | 2500 | 0.0136          |
| 0.0129        | 0.8829 | 3000 | 0.0131          |


### Framework versions

- Transformers 4.41.0
- Pytorch 2.2.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1