---
library_name: peft
license: mit
base_model: vidore/ColSmolVLM-Instruct-500M-base
tags:
- generated_from_trainer
model-index:
- name: colSmol-500M_ufo
  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. -->

# colSmol-500M_ufo

This model is a fine-tuned version of [vidore/ColSmolVLM-Instruct-500M-base](https://huggingface.co/vidore/ColSmolVLM-Instruct-500M-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0878

## 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: 8
- seed: 42
- 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

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.1306        | 0.1636 | 80   | 0.1418          |
| 0.0751        | 0.3272 | 160  | 0.1086          |
| 0.0823        | 0.4908 | 240  | 0.0912          |
| 0.0513        | 0.6544 | 320  | 0.0887          |
| 0.0475        | 0.8180 | 400  | 0.0865          |
| 0.0572        | 0.9816 | 480  | 0.0878          |


### Framework versions

- PEFT 0.15.2
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.3.1
- Tokenizers 0.21.0