---
license: apache-2.0
base_model: dandelin/vilt-b32-mlm
tags:
- generated_from_trainer
model-index:
- name: vilt_finetuned_200
  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_finetuned_200

This model is a fine-tuned version of [dandelin/vilt-b32-mlm](https://huggingface.co./dandelin/vilt-b32-mlm) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 4.3306

## 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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 363.9675      | 0.16  | 100  | 26.1215         |
| 11.4975       | 0.32  | 200  | 7.2332          |
| 6.1909        | 0.48  | 300  | 5.9332          |
| 5.2134        | 0.64  | 400  | 5.5186          |
| 5.0189        | 0.8   | 500  | 5.3268          |
| 4.7551        | 0.96  | 600  | 5.0921          |
| 4.5394        | 1.12  | 700  | 4.9538          |
| 4.3441        | 1.28  | 800  | 4.8967          |
| 4.1436        | 1.44  | 900  | 4.7419          |
| 4.1847        | 1.6   | 1000 | 4.6581          |
| 4.0116        | 1.76  | 1100 | 4.5915          |
| 3.918         | 1.92  | 1200 | 4.5202          |
| 3.8251        | 2.08  | 1300 | 4.4634          |
| 3.7981        | 2.24  | 1400 | 4.4169          |
| 3.7108        | 2.4   | 1500 | 4.3954          |
| 3.5706        | 2.56  | 1600 | 4.3626          |
| 3.5559        | 2.72  | 1700 | 4.3374          |
| 3.6951        | 2.88  | 1800 | 4.3306          |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1