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fine-tuned-for-notes
This model is a fine-tuned version of vidore/colpali-v1.2-hf on an unknown 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: 8e-05
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH 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: 50
- num_epochs: 1
Training results
Framework versions
- PEFT 0.15.1
- Transformers 4.51.1
- Pytorch 2.6.0+cu126
- Tokenizers 0.21.1
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Model tree for amnnsharma/fine-tuned-for-notes
Base model
google/paligemma-3b-pt-448
Finetuned
vidore/colpaligemma-3b-pt-448-base
Finetuned
vidore/colpali-v1.2-hf