---
library_name: transformers
license: apache-2.0
base_model: HuggingFaceTB/SmolVLM-Instruct
tags:
- generated_from_trainer
model-index:
- name: SmolVLM-Instruct-med-vqav1
  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. -->

# SmolVLM-Instruct-med-vqav1

This model is a fine-tuned version of [HuggingFaceTB/SmolVLM-Instruct](https://huggingface.co/HuggingFaceTB/SmolVLM-Instruct) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1712

## 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: 0.001
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_HF 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: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.3885        | 0.4454 | 100  | 0.2168          |
| 0.1862        | 0.8909 | 200  | 0.1728          |
| 0.1258        | 1.3341 | 300  | 0.1678          |
| 0.1131        | 1.7795 | 400  | 0.1615          |
| 0.0885        | 2.2227 | 500  | 0.1682          |
| 0.0656        | 2.6682 | 600  | 0.1712          |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.0
- Tokenizers 0.21.0