---
license: apache-2.0
base_model: dandelin/vilt-b32-finetuned-vqa
tags:
- generated_from_trainer
model-index:
- name: ViLT_Binary_Classifier_Abstract_Scenes
  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. -->

# ViLT_Binary_Classifier_Abstract_Scenes

This model is a fine-tuned version of [dandelin/vilt-b32-finetuned-vqa](https://huggingface.co/dandelin/vilt-b32-finetuned-vqa) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3099

## 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: 0.0005
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.4285        | 0.08  | 100  | 1.4508          |
| 1.4158        | 0.17  | 200  | 1.6115          |
| 1.4004        | 0.25  | 300  | 1.3504          |
| 1.3907        | 0.34  | 400  | 1.3577          |
| 1.3568        | 0.42  | 500  | 1.3397          |
| 1.3562        | 0.5   | 600  | 1.3216          |
| 1.3566        | 0.59  | 700  | 1.3190          |
| 1.3255        | 0.67  | 800  | 1.3227          |
| 1.341         | 0.76  | 900  | 1.3411          |
| 1.3654        | 0.84  | 1000 | 1.3144          |
| 1.3343        | 0.92  | 1100 | 1.3099          |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2