MEDVQACpaligemma
This model is a fine-tuned version of google/paligemma-3b-pt-224 on the arrow 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: 3
Training results
Framework versions
- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.3.1
- Datasets 2.19.1
- Tokenizers 0.19.1
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Model tree for SushantGautam/MEDVQACpaligemma-adapter
Base model
google/paligemma-3b-pt-224