---
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
- f1
model-index:
- name: got-model
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: test
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.09523809523809523
    - name: F1
      type: f1
      value: 0.016563146997929608
---

<!-- 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. -->

# got-model

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co./google/vit-base-patch16-224-in21k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: nan
- Accuracy: 0.0952
- F1: 0.0166

## 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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.0           | 1.0   | 42   | nan             | 0.0952   | 0.0166 |
| 0.0           | 2.0   | 84   | nan             | 0.0952   | 0.0166 |
| 0.0           | 3.0   | 126  | nan             | 0.0952   | 0.0166 |
| 0.0           | 4.0   | 168  | nan             | 0.0952   | 0.0166 |
| 0.0           | 5.0   | 210  | nan             | 0.0952   | 0.0166 |
| 0.0           | 6.0   | 252  | nan             | 0.0952   | 0.0166 |
| 0.0           | 7.0   | 294  | nan             | 0.0952   | 0.0166 |
| 0.0           | 8.0   | 336  | nan             | 0.0952   | 0.0166 |
| 0.0           | 9.0   | 378  | nan             | 0.0952   | 0.0166 |
| 0.0           | 10.0  | 420  | nan             | 0.0952   | 0.0166 |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3