transformers safetensors vit image-classification generated_from_trainer dataset:imagefolder base_model:google/vit-base-patch16-224-in21k license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- f1
model-index:
- name: vit-base-patch16-224-in21k
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: train
      args: default
    metrics:
    - name: F1
      type: f1
      value: 0.960503161050642
---

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# vit-base-patch16-224-in21k

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: 0.0377
- F1: 0.9605

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.1855        | 0.99  | 53   | 0.1819          | 0.4851 |
| 0.1147        | 1.99  | 107  | 0.1140          | 0.7505 |
| 0.1075        | 3.0   | 161  | 0.0932          | 0.8654 |
| 0.0755        | 4.0   | 215  | 0.0684          | 0.9268 |
| 0.0605        | 4.99  | 268  | 0.0584          | 0.9294 |
| 0.0475        | 5.99  | 322  | 0.0436          | 0.9550 |
| 0.0442        | 7.0   | 376  | 0.0503          | 0.9367 |
| 0.0464        | 8.0   | 430  | 0.0398          | 0.9599 |
| 0.0267        | 8.99  | 483  | 0.0445          | 0.9423 |
| 0.0374        | 9.86  | 530  | 0.0377          | 0.9605 |


### Framework versions

- Transformers 4.37.2
- Pytorch 1.12.1+cu102
- Datasets 2.16.1
- Tokenizers 0.15.1
