finetune_colpali_v1_2-swx-4bit
This model is a fine-tuned version of vidore/colpaligemma-3b-pt-448-base on the ManoharPalanisamy/swx-allpages-ColPali dataset. It achieves the following results on the evaluation set:
- Loss: 0.0987
- Model Preparation Time: 0.0048
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: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Use 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: 100
- num_epochs: 1.5
Training results
Training Loss | Epoch | Step | Validation Loss | Model Preparation Time |
---|---|---|---|---|
No log | 0.0183 | 1 | 0.1518 | 0.0048 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.2.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
Model tree for ManoharPalanisamy/finetune_colpali_v1_2-swx-4bit
Base model
google/paligemma-3b-pt-448
Finetuned
vidore/colpaligemma-3b-pt-448-base