---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: Tb_Dataset
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: validation
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.875
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Tb_Dataset

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: 0.4037
- Accuracy: 0.875

## 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: 0.0002
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.0996        | 0.3067 | 100  | 1.0429          | 0.5625   |
| 0.0481        | 0.6135 | 200  | 0.5665          | 0.8125   |
| 0.0391        | 0.9202 | 300  | 1.0037          | 0.6875   |
| 0.0711        | 1.2270 | 400  | 0.5200          | 0.875    |
| 0.0258        | 1.5337 | 500  | 0.3818          | 0.9375   |
| 0.0547        | 1.8405 | 600  | 0.3415          | 0.9375   |
| 0.0029        | 2.1472 | 700  | 0.0637          | 0.9375   |
| 0.0543        | 2.4540 | 800  | 0.7362          | 0.8125   |
| 0.0265        | 2.7607 | 900  | 1.0917          | 0.75     |
| 0.0017        | 3.0675 | 1000 | 0.0030          | 1.0      |
| 0.0054        | 3.3742 | 1100 | 0.0364          | 1.0      |
| 0.0234        | 3.6810 | 1200 | 0.2310          | 0.875    |
| 0.0076        | 3.9877 | 1300 | 0.4037          | 0.875    |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1