---
library_name: peft
license: gemma
base_model: google/paligemma2-28b-pt-448
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: PG2-28b-pt-448-COND_GEN
  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. -->

# PG2-28b-pt-448-COND_GEN

This model is a fine-tuned version of [google/paligemma2-28b-pt-448](https://huggingface.co/google/paligemma2-28b-pt-448) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4487
- Accuracy: 0.7

## 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: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Use 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_steps: 2
- num_epochs: 2

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.3753        | 0.2222 | 400  | 0.3052          | 0.7      |
| 0.2667        | 0.4444 | 800  | 0.2497          | 0.73     |
| 0.3405        | 0.6667 | 1200 | 0.2686          | 0.685    |
| 0.2995        | 0.8889 | 1600 | 0.2595          | 0.735    |
| 0.0841        | 1.1111 | 2000 | 0.4457          | 0.725    |
| 0.1271        | 1.3333 | 2400 | 0.3524          | 0.72     |
| 0.0906        | 1.5556 | 2800 | 0.4202          | 0.69     |
| 0.0532        | 1.7778 | 3200 | 0.4716          | 0.68     |
| 0.1139        | 2.0    | 3600 | 0.4487          | 0.7      |


### Framework versions

- PEFT 0.14.0
- Transformers 4.48.0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0