paligemma_vqav2_vizwiz
This model is a fine-tuned version of [ebrukilic/finetuned_paligemma_vqav2] and this model's base model is: google/paligemma-3b-pt-448 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7363
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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.PAGED_ADAMW with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.0044 | 0.2354 | 200 | 0.9156 |
| 0.8581 | 0.4709 | 400 | 0.8298 |
| 0.8265 | 0.7063 | 600 | 0.7917 |
| 0.7331 | 0.9417 | 800 | 0.7732 |
| 0.664 | 1.1766 | 1000 | 0.7586 |
| 0.7903 | 1.4120 | 1200 | 0.7453 |
| 0.7726 | 1.6474 | 1400 | 0.7387 |
| 0.6803 | 1.8829 | 1600 | 0.7363 |
Framework versions
- PEFT 0.18.0
- Transformers 4.57.3
- Pytorch 2.9.0+cu126
- Datasets 4.4.2
- Tokenizers 0.22.1