---
base_model: uitnlp/visobert
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: d-filter-v1.2
  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. -->

# d-filter-v1.2

This model is a fine-tuned version of [uitnlp/visobert](https://huggingface.co/uitnlp/visobert) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0881
- Accuracy: 0.9668
- F1: 0.8703
- Precision: 0.9044
- Recall: 0.8388

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- 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 | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.1015        | 1.0   | 1414 | 0.0881          | 0.9668   | 0.8703 | 0.9044    | 0.8388 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.17.0
- Tokenizers 0.19.1