paligemma_vqav2
This model is a fine-tuned version of google/paligemma-3b-pt-224 on the vq_av2 dataset.
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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2
- num_epochs: 2
Training results
Framework versions
- PEFT 0.8.2
- Transformers 4.45.0.dev0
- Pytorch 2.2.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1