---
library_name: transformers
license: mit
base_model: vidore/ColSmolVLM-Instruct-500M-base
tags:
- colpali
- generated_from_trainer
model-index:
- name: IndoColSmol-500M
  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. -->

# IndoColSmol-500M

This model is a fine-tuned version of [vidore/ColSmolVLM-Instruct-500M-base](https://huggingface.co/vidore/ColSmolVLM-Instruct-500M-base) on the ingenio/indodvqa_dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3641

## 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: 32
- eval_batch_size: 32
- seed: 42
- 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_ratio: 0.1
- num_epochs: 2

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| No log        | 0.0099 | 1    | 0.4474          |
| 0.4523        | 0.3960 | 40   | 0.4055          |
| 0.3996        | 0.7921 | 80   | 0.3804          |
| 0.3637        | 1.1881 | 120  | 0.3687          |
| 0.345         | 1.5842 | 160  | 0.3627          |
| 0.3466        | 1.9802 | 200  | 0.3630          |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.1
- Tokenizers 0.21.1