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---
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
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