---
license: apache-2.0
base_model: dandelin/vilt-b32-mlm
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: vilt_finetuned_2
  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_2

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: 3.3663
- F1: 0.6000
- Roc Auc: 0.7866
- Accuracy: 0.5735

## 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: 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| 44.1455       | 1.0   | 129  | 6.5479          | 0.1270 | 0.5367  | 0.0735   |
| 2.9608        | 2.0   | 258  | 2.7634          | 0.4385 | 0.6965  | 0.3934   |
| 2.3046        | 3.0   | 387  | 2.4919          | 0.4948 | 0.7204  | 0.4412   |
| 1.895         | 4.0   | 516  | 2.3418          | 0.5652 | 0.7627  | 0.5257   |
| 1.4785        | 5.0   | 645  | 2.6462          | 0.5720 | 0.7701  | 0.5404   |
| 1.1491        | 6.0   | 774  | 2.8805          | 0.6074 | 0.7884  | 0.5772   |
| 0.8297        | 7.0   | 903  | 3.1832          | 0.5977 | 0.7866  | 0.5735   |
| 0.7249        | 8.0   | 1032 | 3.2679          | 0.6054 | 0.7903  | 0.5809   |
| 2.1554        | 9.0   | 1161 | 3.2926          | 0.6119 | 0.7940  | 0.5846   |
| 0.5323        | 10.0  | 1290 | 3.3663          | 0.6000 | 0.7866  | 0.5735   |


### Framework versions

- Transformers 4.40.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2