---
library_name: transformers
license: gemma
base_model: vidore/colpaligemma-3b-pt-448-base
tags:
- colpali
- generated_from_trainer
model-index:
- name: finetune_colpali-v1_3-4bit
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# finetune_colpali-v1_3-4bit

This model is a fine-tuned version of [vidore/colpaligemma-3b-pt-448-base](https://huggingface.co/vidore/colpaligemma-3b-pt-448-base) on the RowekBrah/ColPali_ann_rep_v1_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0578
- Model Preparation Time: 0.0053

## 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: 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: 100
- num_epochs: 1.5

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Model Preparation Time |
|:-------------:|:------:|:----:|:---------------:|:----------------------:|
| No log        | 0.0021 | 1    | 0.2008          | 0.0053                 |
| 0.3933        | 0.2131 | 100  | 0.0982          | 0.0053                 |
| 0.2806        | 0.4262 | 200  | 0.0829          | 0.0053                 |
| 0.2602        | 0.6393 | 300  | 0.0680          | 0.0053                 |
| 0.2336        | 0.8524 | 400  | 0.0635          | 0.0053                 |
| 0.1987        | 1.0639 | 500  | 0.0632          | 0.0053                 |
| 0.1185        | 1.2770 | 600  | 0.0585          | 0.0053                 |
| 0.2225        | 1.4901 | 700  | 0.0574          | 0.0053                 |


### Framework versions

- Transformers 4.50.0
- Pytorch 2.6.0+cu124
- Datasets 3.4.1
- Tokenizers 0.21.1