Model description
This model is a fine-tuned version of google/paligemma-3b-pt-224 on ariG23498/intersection-dataset.
Training procedure
Finetuning done using (LoRA) PEFT method. Rank = 8 choosen.
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Use OptimizerNames.ADAMW_BNB 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
Framework versions
- PEFT 0.14.0
- Transformers 4.50.2
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1
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Model tree for MLap/paligemma_intersections
Base model
google/paligemma-3b-pt-224