---
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: best-model
  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. -->

# best-model

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5533
- Accuracy: 0.8289
- Precision: 0.8457
- Recall: 0.8289
- F1: 0.8320
- Precision Indoor: 0.6897
- Recall Indoor: 0.8696
- F1 Indoor: 0.7692
- Support Indoor: 23
- Precision Notapplicable: 0.8182
- Recall Notapplicable: 0.6923
- F1 Notapplicable: 0.75
- Support Notapplicable: 13
- Precision Outdoor: 0.9444
- Recall Outdoor: 0.85
- F1 Outdoor: 0.8947
- Support Outdoor: 40

## 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: 0.01
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     | Precision Indoor | Recall Indoor | F1 Indoor | Support Indoor | Precision Notapplicable | Recall Notapplicable | F1 Notapplicable | Support Notapplicable | Precision Outdoor | Recall Outdoor | F1 Outdoor | Support Outdoor |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:----------------:|:-------------:|:---------:|:--------------:|:-----------------------:|:--------------------:|:----------------:|:---------------------:|:-----------------:|:--------------:|:----------:|:---------------:|
| No log        | 1.0   | 19   | 0.9758          | 0.7237   | 0.8166    | 0.7237 | 0.7386 | 0.7059           | 0.5217        | 0.6       | 23             | 0.4483                  | 1.0                  | 0.6190           | 13                    | 1.0               | 0.75           | 0.8571     | 40              |
| 0.9607        | 2.0   | 38   | 0.5533          | 0.8289   | 0.8457    | 0.8289 | 0.8320 | 0.6897           | 0.8696        | 0.7692    | 23             | 0.8182                  | 0.6923               | 0.75             | 13                    | 0.9444            | 0.85           | 0.8947     | 40              |


### Framework versions

- Transformers 4.57.6
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.2