paligemma_vqa_lower
This model is a fine-tuned version of google/paligemma-3b-pt-224 on the vq_av2 dataset. It achieves the following results on the evaluation set:
- Loss: 0.0122
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 |
|---|---|---|---|
| 4.837 | 0.1471 | 500 | 3.7992 |
| 0.1673 | 0.2943 | 1000 | 0.1149 |
| 0.0227 | 0.4414 | 1500 | 0.0198 |
| 0.0146 | 0.5886 | 2000 | 0.0138 |
| 0.0135 | 0.7357 | 2500 | 0.0125 |
| 0.013 | 0.8829 | 3000 | 0.0122 |
Framework versions
- Transformers 4.41.0
- Pytorch 2.2.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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Model tree for statking/paligemma_vqa_lower
Base model
google/paligemma-3b-pt-224