---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- fl_image_category_ds
metrics:
- accuracy
base_model: google/vit-base-patch16-224-in21k
model-index:
- name: project_name
  results:
  - task:
      type: image-classification
      name: Image Classification
    dataset:
      name: fl_image_category_ds
      type: fl_image_category_ds
      config: default
      split: train
      args: default
    metrics:
    - type: accuracy
      value: 0.6621621621621622
      name: Accuracy
---

<!-- 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. -->

# project_name

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 fl_image_category_ds dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9537
- Accuracy: 0.6622

## 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: 5e-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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3368        | 1.0   | 88   | 1.2575          | 0.5448   |
| 1.1146        | 2.0   | 176  | 1.0928          | 0.6038   |
| 0.9667        | 3.0   | 264  | 1.0195          | 0.6223   |
| 0.9005        | 4.0   | 352  | 0.9832          | 0.6373   |
| 0.8432        | 5.0   | 440  | 0.9537          | 0.6622   |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.1
- Datasets 2.8.0
- Tokenizers 0.13.2