---
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: wmc-wmk811-v0-vit-special_map_det_0917
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# wmc-wmk811-v0-vit-special_map_det_0917

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co./google/vit-base-patch16-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0354
- Accuracy: 0.9882
- Precision: 0.9872
- Recall: 0.9854
- F1: 0.9863

## 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
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.0471        | 0.2158 | 400  | 0.0651          | 0.9766   | 0.9793    | 0.9662 | 0.9724 |
| 0.0664        | 0.4317 | 800  | 0.0445          | 0.9874   | 0.9879    | 0.9828 | 0.9853 |
| 0.0391        | 0.6475 | 1200 | 0.0476          | 0.9833   | 0.9826    | 0.9785 | 0.9805 |
| 0.0478        | 0.8633 | 1600 | 0.0354          | 0.9882   | 0.9872    | 0.9854 | 0.9863 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1